Memory Gc

memory-gc

Daily garbage collection pass for the Hermes memory system. Read this whole skill before taking any action. Execute steps in order. Use the memory tool for MEMORY.md / USER.md mutations; use the terminal for filesystem pruning.

Inputs you already have

• MEMORY.md and USER.md are already in your system prompt (the snapshot shown at the top of this session). Read them there. Each entry looks like:

  [YYYY-MM-DD][cat] content
  

Tool availability

The memory tool IS available in cron (toolset enabled, config has memory_enabled:true). Use it normally. If it returns "Memory is not available", fall back to direct file editing via FilePatch on ~/.hermes/memories/MEMORY.md.

Pitfall — MemoryStore target values: Current Hermes memory tool schemas may expose target as "memory" (for MEMORY.md) and "user" (for USER.md); older runtimes or docs may refer to "MemoryStore". Use the target names from the live tool schema first. If MEMORY writes fail with target/remapping errors, use FilePatch directly on ~/.hermes/memories/MEMORY.md instead. The "user" target works reliably.

Pitfall — serial hot-memory mutations: Do not parallelize multiple memory tool mutations against the same target when capacity, separators, or later old_text matches depend on the previous mutation. The tool returns a fresh snapshot after each write; parallel removals/replacements can race or make the reported usage misleading. Archive removals in one Python pass if useful, then run memory remove/replace/add calls serially for MEMORY.md or USER.md.

When using FilePatch:

• Remove entries by replacing the entry text AND its trailing § separator line together in one replacement (match <entry text>\n§ → empty string). This avoids orphaned separators.
• If the entry is the LAST in the file (no trailing §), remove just the entry text and the preceding \n§\n from the entry above it.
• Clean up resulting blank lines with portable Python afterward:

python3 - <<'PY'
from pathlib import Path
p = Path.home() / '.hermes/memories/MEMORY.md'
p.write_text('\n'.join(l for l in p.read_text().splitlines() if l.strip()) + '\n')
PY

• The same safety rails apply: never touch [rule] or [meta] entries.

Pitfall — multibyte characters: MEMORY.md may contain unicode (arrows, special chars in old entries). Use Python for age computation rather than awk, which chokes on multibyte sequences in some locales.

Pitfall — block removal sweeps interleaved keepers (DATA LOSS): When removing 2+ entries via a single block-replace, NEVER assume the block is homogeneous. Non-target entries (especially [rule] / [meta]) are often interleaved between the entries you want gone. A whole-block old_string → condensed new_string will silently delete every interleaved keeper. Before any block replace: read the EXACT lines in the block (FileRead the range, do not trust memory), confirm every entry in old_string is genuinely a removal target, and copy any interleaved keepers verbatim into new_string. After the patch, grep -c for a distinctive phrase from each keeper to verify it survived. This bit during a topic-pointer consolidation: two [rule] entries sat between the pointers and were swept up; they had to be restored in a follow-up patch.

Pitfall — FilePatch § uniqueness: The § separator appears on every entry boundary. old_string containing just <text>\n§ will often match multiple locations. Always include enough surrounding context (adjacent entry text on both sides) to make the match unique. Alternatively, batch multiple adjacent removals into a single FilePatch that replaces the whole multi-entry block at once — this is more reliable than individual removals and is the PREFERRED approach when removing 2+ entries. Include the preceding entry's text as an anchor in old_string and keep it in new_string.

Pitfall — last entry has no trailing §: The final entry in MEMORY.md typically has no § after it. When removing the last entry, your replacement must also consume the §\n that preceded it (from the second-to-last entry's separator). When removing a middle entry, consume it plus its trailing \n§\n. Always verify with tail -5 after patching to confirm no orphaned separators or missing newlines.

Pitfall — malformed separators (concatenated §): Occasionally the § separator gets concatenated to the end of an entry line instead of appearing on its own line (e.g., ...fallback.§ instead of ...fallback.\n§). When you encounter this during removal or relocation, fix the formatting in the same FilePatch operation: split the concatenated § onto its own line. If removing the entry, just include the malformed form in old_string. If keeping adjacent entries, normalize the separator. Detect early with: grep '.\§' ~/.hermes/memories/MEMORY.md (any non-newline char before §).

Pitfall — pending drain in cron: The memory tool IS available in cron. Always drain pending. Never skip it.

Pitfall — memory tool threat scanner: The memory tool may block otherwise safe replacements if the new content contains sensitive-path patterns such as exact secret-file paths. When shortening or normalizing existing memory entries, preserve the meaning with safer generalized wording (e.g. "source env files" instead of naming a private env file) rather than falling back to direct file edits. Do not bypass scanner blocks for entries involving secrets.

Pitfall — shell writes blocked by git guard: Dedicated memory files (~/.hermes/memories/*.md) live inside a git-tracked directory. Shell write commands like cat >> or heredocs can be intercepted by the block-dangerous-merges plugin, which scans shell commands for git-like patterns and may false-positive on writes to tracked paths. Always use FilePatch (mode=replace, extending the last line) to append to dedicated memory files. This bypasses shell interception entirely.

Pitfall — all-or-nothing patches: FilePatch validates every hunk before writing. One no-op hunk (old text identical to new text) or stale hunk aborts the entire multi-file patch, even if the other hunks are good. For large memory shortening passes, remove no-op hunks before submitting, or split risky edits into smaller patches so one stale line does not cancel the whole pass.

Decay rules (from the [meta] Memory format entry)

"Review" = a judgment call by you. Err on the side of keeping. When removing, log the removal in the final report.

Archival logging (ALL removals — deduplicated)

Before deleting ANY entry — whether a step-2 hard drop, a step-3 review removal, a step-4 pending discard, or a step-8 capacity eviction — append its full content to ~/.hermes/episodes/.gc.log so nothing is truly lost. The archive must be deduplicated: never write an entry whose content already exists in .gc.log.

Use this helper for every removal. It is idempotent — calling it twice with the same content writes only once:

gc_archive() {  # usage: gc_archive "<full entry text>"
  local entry="$1"
  local log="$HOME/.hermes/episodes/.gc.log"
  touch "$log"
  # Dedup: skip if this exact entry body is already archived (fixed-string match)
  grep -Fqx "$entry" "$log" || printf '%s\n' "$entry" >> "$log"
}

For batch removals, collect the bodies and archive them in one pass, still deduplicated:

python3 - <<'PY'
from pathlib import Path
log = Path.home() / '.hermes/episodes/.gc.log'
log.touch()
existing = set(log.read_text().splitlines())
removed = [
    # paste full entry bodies being removed this run, one string each
]
with log.open('a') as f:
    for e in removed:
        if e not in existing:
            f.write(e + '\n')
            existing.add(e)
PY

Run the appropriate archive step IMMEDIATELY before each removal/discard below. The capacity-eviction log in step 8 is now subsumed by this rule (still dedup before appending). Do NOT copy archived entries back into .pending.md or MEMORY.md — .gc.log is a one-way archive, not a re-injection source.

Procedure

1. Compute ages

For each entry in MEMORY.md and USER.md, parse the leading [YYYY-MM-DD] and compute the age in days relative to today. Skip any entry without a parseable date — report it as unparseable.

USER.md core profile exception: USER.md often starts with a prose profile block before the first §. Treat that first non-dated block as expected core profile, not a parse anomaly. Only report unparseable dated-entry areas below the core profile separator.

Also detect malformed separators: grep '.\§' ~/.hermes/memories/MEMORY.md. Fix any concatenated § characters (entry text with § appended without newline) during the first FilePatch operation that touches the affected area.

If only a few MEMORY.md or USER.md entries are unparseable while the rest of the file parses, do not stop the whole run. Treat them as malformed hot-memory entries: archive the full text first, then either normalize them into a dated entry if the category is obvious or, preferably, relocate durable project/runtime content into the relevant topic file and remove it from hot memory. For USER.md below the core profile separator, use memory target user with action: replace when the entry is merely missing a leading date/category. Keep the user preference intact, add the earliest defensible date visible inside the malformed text, and re-check parsing after the patch. If USER.md is slightly over its 5000-char limit because of that malformed entry, it is still safe to normalize/shorten that one entry as part of parse repair; do not treat this as permission to rewrite the core profile or run a broad USER preference consolidation.

2. Apply hard drops (no review, no judgment)

• [tmp] entries older than 7 days → memory tool, action: remove, old_text = shortest unique substring.
• [proj:<path-or-namespace>] entries where the tag is explicitly an absolute filesystem path (or ~ expanded against the current home) and that resolved path does not exist on disk → archive + remove. Do not hard-drop proj:./... or proj:../... merely by resolving them against the GC process cwd; cron may run from ~/.hermes, not the original project. Only prune a relative project tag after resolving it against a known/stored project root captured with the memory entry. If no such base is available, treat it like a namespace and review/relocate by content. Namespace-only project tags such as proj:<name>-wiki, proj:<name>-agent, or proj:<name> are not path checks; review them by content and keep/relocate if still useful.

3. Apply review rules

For each entry past its review threshold (from the table above):

• If it's still plausibly accurate / still used → keep.
• If it is obviously stale (refers to resolved tmp state, abandoned project, superseded decision) → remove.

Confidence gate (capacity-aware): Check wc -c ~/.hermes/memories/MEMORY.md against 70% of the configured memory_char_limit (read it from config — see step 8; e.g. limit 8000 → 5600).

• If MEMORY.md is OVER the 70% target: "Unsure" = evict. The system will re-extract from future sessions if it matters.
• If MEMORY.md is UNDER the 70% target: "Unsure" = keep. There's room, no harm.

Dedicated memory file check: Before keeping a [proj:*] entry, check if a dedicated file exists at ~/.hermes/memories/ that covers the same project (e.g., <project-a>.md, <project-b>.md, <service>.md, INFRASTRUCTURE.md). If the entry's content is already in that file, remove it from MEMORY.md — it's redundant. If the entry contains NEW info not yet in the dedicated file, MOVE it there (append to the appropriate section) then remove from MEMORY.md. This "relocate" pattern is the best way to reclaim MEMORY.md capacity without losing information.

4. Triage .pending.md (prune BEFORE draining)

First, run the deterministic dedup script to remove obvious duplicates. If the runtime has not installed ~/.hermes/scripts/dedup-pending.py, use the inline fallback below rather than failing the GC run:

if [ -x ~/.hermes/scripts/dedup-pending.py ]; then
  python3 ~/.hermes/scripts/dedup-pending.py
else
  python3 - <<'PY'
from pathlib import Path
p = Path.home() / '.hermes/episodes/.pending.md'
if p.exists():
    seen = set(); out = []
    for line in p.read_text().splitlines():
        if line and line not in seen:
            seen.add(line); out.append(line)
    p.write_text('\n'.join(out) + ('\n' if out else ''))
PY
fi

Then check what remains:

test -s ~/.hermes/episodes/.pending.md && wc -l ~/.hermes/episodes/.pending.md

If pending > 100 lines, run a manual prune pass FIRST. The session-end plugin has no awareness of existing memory and will re-extract known facts every session. Expect massive duplication (same project fact repeated 10-50x with slight rephrasing). The dedup script catches exact duplicates but misses semantic duplicates (same fact rephrased differently), so expect ~0 removals from the script even with 100+ duplicate entries.

Preferred: scripted semantic prune. Use the proven two-pass script at scripts/prune_pending.py (in this skill's directory):

SKILL_DIR="${SKILL_DIR:-$HOME/.hermes/skills/memory-gc}"
python3 "$SKILL_DIR/scripts/prune_pending.py"

If your runtime exposes the loaded skill directory under a different variable or path, set SKILL_DIR to that memory-gc/ folder first. The script is bundled inside this skill; do not use a path with an extra category directory unless you actually installed it there.

Pass 1 hard-drops [tmp] entries, stale/completed [task] entries, and rule minutiae, then deduplicates within each category by topic key (keeps longest per topic). Pass 2 collapses cross-category namespace sprawl (the #1 duplication source: a single project may generate entries under proj:<name>, proj:<name>-wiki, proj:<name>-agent, proj:<name>/<subdir>, proj:<name>-cli, proj:<name>-site — all one project).

Target: Prune to <50 entries. For files of 100-200 lines, expect 84% removal (191→31 proven). For 600+ lines, expect the script to reach ~50-100 entries after expanded generic-rule and transient-fact filtering (updated May 2026 to drop common coding patterns like error handling, XSS, race conditions, validation, CI patterns, and transient operational facts like ad metrics and PR statuses). If still >50 after the script, a short inline Python pass targeting remaining PR-specific facts and project-detail duplicates typically closes the gap.

If the prune script still leaves >100 lines, do NOT drain them into MEMORY.md. Treat that as semantic-prune miss, then run a second manual pass: relocate durable project/runtime facts into dedicated memory files, discard PR/task minutiae, and clear .pending.md. Pending overflow is cheaper to discard than to pollute MEMORY.md or USER.md.

Emergency fast path for 200+ survivors: Use counters before reading the whole file. Count targets/categories/topic keywords, then archive every surviving TARGET\tLINE body individually. Do not hand-drain hundreds of PR statuses into MEMORY.md. Instead, preserve only class-level learning by writing concise grouped sections into the relevant topic files (for example a project's architecture, its data quality, assistant-runtime routing, investing research), then clear pending. If you create or materially update topic files, rebuild INDEX.md, add compact non-empty descriptions for new files that otherwise show (no description), and add only the few hot [meta] Topic file: pointers needed for files created or materially touched this run. This preserves useful architectural/runtime facts without ballooning MEMORY.md.

If the prune script leaves 50-100 entries, do not blindly drain just because it is under the hard stop. Read the survivors and apply the fast path below: relocate durable architectural/runtime facts into dedicated files, discard PR/task/status minutiae, and clear pending. In practice, a 283→80 prune can still contain mostly duplicate project state that belongs in a project topic file (<project-a>.md, <project-b>.md) or INFRASTRUCTURE.md, not MEMORY.md.

If the script's topic keys don't cover a new project, extend the mega_topic function with a new block matching the project's namespace variants.

Fallback manual prune pass (if scripting feels overkill for <50 entries):

1. Count by topic: grep -oE '\[proj:[^]]+\]' .pending.md | sort | uniq -c | sort -rn
2. Nuke duplicates: For any topic with >5 entries, read them all and write ONE consolidated entry per genuinely distinct fact. Discard the rest.
3. Review tasks: Remove [task] entries only when they are past the 14-day review window or clearly completed/abandoned; keep active follow-ups for the normal drain/review path.
4. Kill redundant rules: Remove rules already captured in SOUL.md or MEMORY.md.
5. Kill generic coding rules: Discard ALL rules about language syntax (f-strings, imports, line length), basic git usage (stash, merge conflicts, push after commit), linting/formatting (ruff, eslint), or general software practices (cache keys, error handling, path validation). These are common knowledge, not durable memory. Only keep rules that encode a project-specific convention or a user-specific preference not derivable from first principles.
6. Kill project minutiae: PR numbers, commit SHAs, specific file paths, and intermediate debugging steps are not durable. Keep only architectural decisions.

Then drain the surviving entries:

Fast path — when dedicated files cover most projects: After pruning, if every surviving [proj:*] entry maps to an existing dedicated memory file AND surviving [rule]/[fact] entries are project-specific code rules (not general agent rules), relocate architectural facts to dedicated files and discard everything else. In practice this is the common case: the prune script drops tasks/tmp, and what remains is project-specific detail that belongs in <project-a>.md, <project-b>.md, <service>.md, etc. Batch related facts into a single new subsection per file (e.g., "### Code Rules (May 2026)") rather than appending one entry at a time. After relocation, clear pending with no drain into MEMORY.md.

Relocate before draining -- this is the highest-ROI move. After pruning duplicates, check if surviving [proj:*] entries contain architectural facts that belong in a dedicated memory file (<project-a>.md, <project-b>.md, <service>.md, etc.). If so, append the information as a new subsection to the appropriate dedicated file and discard the pending entry. In practice, a single GC run can relocate 5-10 entries into 2-3 new subsections in a dedicated file, preserving all information without consuming any MEMORY.md capacity. Only entries that don't fit any dedicated file should be candidates for draining into MEMORY.md.

When the prune script leaves a small but still duplicate-heavy survivor set (<50 lines), do a consolidation pass before appending to dedicated files: group same-topic pending lines (e.g. several WhatsApp/Bloom CTA lines, several Modal batch timeout lines) into one concise bullet block per dedicated file. Archive all survivor lines individually before clearing .pending.md, even if only the consolidated version was relocated.

When the prune script still leaves a medium survivor set (~100-200 lines), use the same consolidation pattern instead of hand-draining: archive every survivor body, group by durable topic, append a compact "GC Consolidated Notes" subsection to the relevant topic files, and clear pending. Treat PR status, merge state, and one-off review outcomes as discardable; preserve only class-level rules, durable architecture, routing quirks, and user-approved product decisions. This proved workable on 312→164 and 203→126 pending runs by relocating grouped notes into project, service, runtime, taxonomy, and persona topic files while keeping MEMORY.md at capacity target. After relocation, remove or shorten any redundant hot-memory entry that now duplicates the topic file rather than draining a new hot entry.

Each non-empty line is TARGET\tLINE. Before discarding any line, archive it with gc_archive (deduplicated — see "Archival logging" above). For each line:

• If MEMORY.md already contains the same information (even rephrased) → archive + discard.
• If a dedicated memory file already covers it → archive + discard (it was relocated or already known).
• If it's a stale [task] entry (>14d) → archive + discard.
• If genuinely new and MEMORY.md has room → add via memory tool.
• If no room → archive + discard (it wasn't important enough to survive triage).

The bulk pending discards from the prune script (step 4) are generic rules / PR minutiae and need NOT be archived individually; only archive the entries that survive the prune script and reach this per-line triage. This keeps .gc.log signal-rich rather than flooding it with the 600+ discarded boilerplate entries.

ALWAYS clear the file after processing, even if some entries were discarded:

: > ~/.hermes/episodes/.pending.md

Never leave pending entries to accumulate across runs. If you processed them (even by discarding), the file gets truncated.

Final pending recheck: Memory/tool writes during GC can enqueue a tiny fresh .pending.md tail after the main drain. Before writing the final GC summary, check .pending.md one last time. If new rows appeared, archive each body, relocate any durable class-level fact into the right topic file, clear pending again, rebuild INDEX if topic files changed, then append the summary as the last .gc.log line. Do not leave the new tail for tomorrow.

Contradiction pitfall: The final pending tail can contain newer corrections that contradict facts you just consolidated from the earlier survivor set. Do not blindly archive-and-clear it. If a tail row corrects a relocated note, patch the topic file immediately so the corrected fact wins, then archive and clear the row. This commonly shows up as "root cause was X, not Y" after a large pending consolidation.

5. Consolidate near-duplicates

Scan MEMORY.md and USER.md for entries that say essentially the same thing (different dates or phrasing). Merge into one entry using memory tool action: replace. Keep the earliest creation date.

6. Maintain canonical themes

Collect every tag used in episode files:

grep -h "^tags:" ~/.hermes/episodes/*.md 2>/dev/null \
  | sed 's/^tags:[[:space:]]*//' | tr ',' '\n' | sed 's/^[[:space:]]*//;s/[[:space:]]*$//' \
  | sort | uniq -c | sort -rn

Read the current canonical list from MEMORY.md (the [meta] Episode tags (canonical) entry).

• Any tag used in ≥3 episodes but missing from the canonical list → memory replace to add it to the [meta] entry.
• Near-duplicate tags in use (debug/debugging, cron/crons, skill/skills) → pick one canonical spelling. Note the merge in your final report (episode-file rewrite is future work, not this pass).

Keep the [meta] Episode tags line under ~250 characters. If it starts to bust, switch from additive mode to consolidation mode: replace the canonical line with the highest-signal top-used tags, keep canonical spellings, and drop low-signal or stale tags even if they have historical count. Do not keep expanding an already-overlong canonical line. When consolidating, prefer the most common normalized spellings (e.g., debugging over debug, cron over crons) and include only as many top tags as fit under the cap. It is fine to leave frequently used long-tail tags out if adding them would make the meta entry too long.

Optimization: If the tag output is large and the canonical list hasn't changed recently, scan only the top ~30 tags for missing canonicals. Don't waste tokens on the long tail.

7. Prune old files

Use recoverable deletion. The global runtime bans permanent rm, and find -delete has the same irreversibility problem. Move stale files to ~/.Trash/memory-gc/ instead of deleting them:

python3 - <<'PY'
from pathlib import Path
from datetime import datetime
import shutil
home = Path.home()
trash = home / '.Trash' / 'memory-gc'
trash.mkdir(parents=True, exist_ok=True)
now = datetime.now().timestamp()
for root, pattern, days in [
    (home / '.hermes/episodes', '*.md', 90),
    (home / '.hermes/sessions', '*.jsonl', 180),
]:
    if not root.exists():
        continue
    for p in root.glob(pattern):
        if p.name == '.pending.md':
            continue
        if now - p.stat().st_mtime > days * 86400:
            dest = trash / p.name
            if dest.exists():
                dest = trash / f'{dest.stem}-{int(now)}{dest.suffix}'
            shutil.move(str(p), str(dest))
PY

8. Enforce 70% capacity target

Prefer consolidation over eviction. Before evicting any entry, scan for near-duplicate or overlapping entries that can be merged into one shorter entry preserving both signals. This is especially effective when slightly over target (< 200B) — merging two 250B entries into one 180B entry reclaims space without losing information. Only evict when consolidation alone cannot close the gap.

Shortening entries: When only slightly over target (<100 chars), try shortening wordy [pref] or [env] entries before evicting anything. Remove filler phrases ("in YAML frontmatter" → just parenthetical, "should always be" → "always", "For ad creative cron/jobs, reject" → "Reject"). If MEMORY.md is over target and contains mostly protected [rule] / [meta] entries, shorten those too, but only as lossless compression: preserve dates, categories, force, and behavioral meaning. Never remove [rule] or [meta] entries during GC. This preserves meaning while reclaiming 30-50 chars per entry; a sequence of small rewrites can close a large overage without data loss. Use the memory tool first for MEMORY.md/USER.md. If it blocks on scanner safety, rewrite the replacement with less sensitive wording rather than bypassing it.

After all removals and drains, check the current size of MEMORY.md AND read the configured limit from config (do NOT hardcode it — it has changed before, e.g. 6000 → 8000 in June 2026):

wc -c ~/.hermes/memories/MEMORY.md
LIMIT=$(python3 - <<'PY'
from pathlib import Path
import re
cfg = Path.home() / '.hermes/config.yaml'
limit = ''
if cfg.exists():
    for line in cfg.read_text(encoding='utf-8').splitlines():
        m = re.match(r'\s*memory_char_limit:\s*(\d+)\s*$', line.split('#', 1)[0])
        if m:
            limit = m.group(1)
            break
print(limit or '8000')
PY
)
echo "limit=$LIMIT target(70%)=$((LIMIT*70/100))"

Fresh agent-agnostic installs may not have ~/.hermes/config.yaml or a memory_char_limit key yet. In that case, fail closed to the documented default limit of 8000 chars rather than treating an empty $LIMIT as zero and evicting all unprotected memory.

The target is 70% of the configured limit (limit 8000 → target 5600; limit 6000 → target 4200). Compute it from $LIMIT, never from a memorized number. GC must always leave the file below 100% of the limit — parking at 99% is the exact failure mode this step exists to prevent.

Topic-pointer demotion (the #1 bloat source — do this BEFORE eviction). [meta] Topic file: X = ... pointers duplicate INDEX.md, which recall reads first. They are hot-route hints, not storage. Keep only pointers for topic files created, modified, or heavily used in the last ~7 days; cap the total at ~5. For every other pointer: confirm the file is in INDEX.md (grep -F '<file>.md' ~/.hermes/memories/INDEX.md), archive the pointer with gc_archive, then remove it. This is the Claude-Code Dream Phase-4 pattern (index holds pointers; hot memory does not) and reclaims ~90 bytes per pointer with zero information loss. Run it every pass so hot memory cannot drift back up. Note: [meta] pointers are normally protected, but topic-pointer demotion is an explicit exception — you are relocating the pointer to INDEX, not deleting info.

If the file still exceeds the target after pointer demotion, evict entries. Eviction priority (evict from top priority first):

1. [env] entries older than 21 days (even if still accurate; they can be re-added if needed)
2. [proj:*] entries older than 14 days
3. [fact] entries older than 45 days
4. Longest entries first (within the same priority tier)

When no entries meet age thresholds but file is over target: Fall back to evicting the longest [env] entries first, then longest [proj:*] entries, regardless of age. Prefer entries whose content is also captured in a dedicated memory file (e.g., ~/.hermes/memories/<project>.md) or in a skill, since those can be re-derived.

[pref] relocation (the file-stays-at-98% failure mode). A hot-memory file dominated by [rule] + [meta] + long project [pref] entries cannot be brought to target by the env/proj/fact ladder above — those are a small slice of the bytes. When the file is still over target after that ladder, treat long project-scoped [pref] entries as relocation candidates (NOT eviction — prefs encode user-approved decisions, so move them, don't drop them):

• If a [pref] is scoped to a project with a dedicated file (e.g. <project-a>.md, <project-b>.md, <service>.md), append its content as a dated bullet to that file's notes section, archive the original with gc_archive, and remove it from MEMORY.md. This is the highest-ROI move when rule/meta/pref dominate — a single run can reclaim 1-2 KB.
• Generic, cross-project [pref] entries stay hot but get the lossless shortening pass (strip filler, keep the decision).
• Never relocate a [rule]; rules are behavioral constraints that must stay in the system prompt every session.

Protected-floor guard (never silently park at 98%). Compute the byte total of [rule] + [meta] entries alone. If that floor already exceeds the 70% target, the target is unreachable without shortening protected entries:

1. Run the lossless-shortening pass on the longest [rule]/[meta] entries (the skill already permits this — preserve dates, categories, force, and behavioral meaning) until the file is under 100% of the limit.
2. Relocate every project-scoped [pref] per the rule above.
3. If the file is STILL over the 70% target after 1-2, do not loop forever — stop at the lowest achievable byte count and flag it explicitly in the final report ("protected floor N chars exceeds 70% target M; durable rule set has outgrown hot memory, consider raising memory_char_limit or splitting rules into SOUL.md"). Parking just-under-limit with a flag is correct here; parking at 98% with no flag is the bug this guard exists to prevent.

Before removing, archive evicted entries to ~/.hermes/episodes/.gc.log using the deduplicated gc_archive helper (see "Archival logging" above). Do NOT copy evicted entries back to .pending.md — this creates a circular feedback loop where entries bounce between MEMORY.md and pending indefinitely.

Keep evicting until the file is at or below the 70% target (computed from $LIMIT above), or only [rule] and [meta] entries remain.

USER.md capacity check: Also check wc -c ~/.hermes/memories/USER.md. USER.md has a 5000-char limit and often runs near capacity (4900-5000). Before draining any user-targeted pending entry, check remaining capacity first. If USER.md is at 95%+ capacity (4750+ chars), skip the drain — the entry will be re-extracted if it matters. Don't waste time trying to make room in USER.md; its core profile section is stable and shouldn't be edited during GC.

USER.md persistently over limit: If USER.md exceeds 5000 chars on two consecutive GC runs, flag it in the report as needing human attention. The core profile (Identity through Temperament) is stable, but the [pref] entries appended at the bottom accumulate. A human pass to consolidate or relocate preferences is the right fix — GC should not autonomously edit the core profile.

USER.md escalation after 4+ runs over limit: If USER.md has been flagged for 4+ consecutive runs (check .gc.log for the pattern), GC may autonomously consolidate [pref] entries at the bottom of USER.md (below the § after Temperament). Rules: (a) never touch the core profile above that §, (b) merge semantically overlapping prefs into one shorter entry keeping the earliest date, (c) relocate project-specific prefs to the project's dedicated memory file if one exists (e.g., Bloom rollout prefs → <project-b>.md), (d) cap total [pref] entries at 6. Log all changes. This is a pressure valve; if the user objects, revert to flag-only.

9. Maintain topic files & INDEX

Topic files (memories/*.md excluding core MEMORY/USER/MEM_ARCH/INDEX and *.bak) are the Tier-2 raw-text store. The session-end plugin can now create them and queues a [meta] Topic file: X.md = ... pointer into .pending.md (drained in step 4). GC keeps the registry and pointers consistent.

a. Archive stale generated-inventory topic files before the routine rebuild. Run the candidate query before refreshing INDEX.md so a just-generated inventory row cannot protect every stale file. INDEX.md remains the authoritative recall registry, but only rows with a human-curated description (not (no description)) count as archival references.

SKILL_DIR="${SKILL_DIR:-$HOME/.hermes/skills/memory-gc}"

# 1. Dry run — print candidates, sanity-check them:
python3 "$SKILL_DIR/scripts/topic_index.py" archive-candidates

# 2. If the list looks right, apply (moves files + rebuilds INDEX):
python3 "$SKILL_DIR/scripts/topic_index.py" archive-candidates --apply

Always run the dry run first and eyeball the list — err on the side of keeping. After --apply, remove any now-orphan [meta] pointer for the archived files via the memory tool (the script prints a reminder).

b. Rebuild INDEX.md from the current topic files after archival and after any topic-file changes. The logic lives in a tested script (scripts/topic_index.py), not inline here:

SKILL_DIR="${SKILL_DIR:-$HOME/.hermes/skills/memory-gc}"
python3 "$SKILL_DIR/scripts/topic_index.py" rebuild-index

It regenerates the registry from disk, preserves existing one-line descriptions, and excludes core files (MEMORY/USER/MEM_ARCH/INDEX), *.bak, and dotfiles. Run it after any topic-file change (drain, relocation, archive).

c. Prune stale published-artifact URLs. If ~/.hermes/memories/artifacts.md exists, validate rows in its registry table during the topic-file maintenance pass. For each row with an http:// or https:// URL, do a cheap HEAD request first and fallback to GET only when HEAD is unsupported. Keep rows that return 2xx/3xx or that fail due to transient network/auth errors. Move rows that clearly return 404/410/NXDOMAIN into a ## Pruned section at the bottom with the prune date instead of deleting them outright. This keeps the auto-populated artifact registry useful without losing the historical trail.

d. Reconcile pointers in MEMORY.md. INDEX.md is the authoritative registry; MEMORY.md pointers are only hot-route hints for high-value or recently touched topic files. Do not add pointers for every topic file when the topic file count is large, because this can blow the 70% hot-memory target. Instead:

• Missing pointer for a topic file you created, modified, or relocated into this run → add one via the memory tool ([<today>][meta] Topic file: <name> = <desc>). Keep descriptions extremely compact (usually 1-3 words).
• Missing pointer for an old untouched topic file → leave it to INDEX.md; do not spend hot-memory capacity on it.
• Duplicate pointers for the same file → consolidate to one (keep earliest date).
• Orphan pointer (points to a file that no longer exists) → remove it. Note: most pointers arrive automatically through the step-4 pending drain; this step just fixes drift for newly touched or stale hot pointers.

Pitfall — schedule/config truth lives in jobs.json, not prose. Cron times, model/provider, and enabled state get duplicated into human docs (INFRASTRUCTURE.md's cron table, MEM_ARCH.md's diagram, SOUL's capacity note, visual-options docs) and drift over time. When reconciling any such fact, the authoritative source is ~/.hermes/cron/jobs.json (the job's schedule.expr), never the prose. memory-gc itself runs at 0 1 * * * (1am); older docs that say "4am" are stale and should be corrected to match the cron, not the reverse. Before "fixing" a doc to agree with another doc, read jobs.json and let it win. Note that the separate claude-code-memory-* topic files describe a Claude Code launchd port that genuinely runs at 4am — those 4am references are correct and must NOT be rewritten to 1am.

Capacity pitfall: Step 8 runs before topic-pointer reconciliation, but adding missing pointers in step 9 can push MEMORY.md back over the 70% target. Budget hot pointers before adding them: if MEMORY.md is already near target, add only the highest-value newly touched pointers and leave the rest to INDEX.md. If you do add multiple pointers, add them one at a time or in a small batch, then immediately rerun wc -c ~/.hermes/memories/MEMORY.md before doing more. After pointer reconciliation, rerun wc -c ~/.hermes/memories/MEMORY.md and, if over target, do a quick lossless shortening pass (prefer wordy [rule], [pref], and pointer descriptions) until MEMORY.md is ≤ the 70% target again. If the file is only slightly over target after all substantive removals, keep using memory action: replace for tiny lossless edits until the byte count is actually under target. Do not stop at “close enough” (e.g. 1 byte over). Good micro-shortening targets are repeated helper words (use, only, globally), long pointer descriptions, long canonical tag lists, and redundant detail that is already in a topic file. If shortening protected entries is not enough, archive and remove redundant [pref]/[fact] entries whose detail now lives in topic files; that is safer than leaving hot memory above target. Count shortening as consolidated, not removed.

Tests for this script live in scripts/test_topic_index.py (python3 scripts/test_topic_index.py — all in a tempdir).

10. Log and report

Canonical log location: The ONLY live GC log is ~/.hermes/episodes/.gc.log. A stale orphan can exist at ~/.hermes/memories/.gc.log (legacy location) and will be frozen at an old date — do not mistake it for evidence that GC stopped running. If you find the orphan, prepend its older entries to the canonical log (if they predate the canonical first line) and trash the orphan so there is a single source of truth. Verify GC health by reading the LAST line of episodes/.gc.log, not by trusting whichever log you happened t

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