Recallloom

RecallLoom

RecallLoom is a portable context harness for session-based agents.

It provides a lightweight file model for project continuity across sessions without requiring heavy infrastructure.

The goal is not to remember everything. The goal is to keep the right project state durable, readable, and recoverable across sessions.

Package Scope

This file is the agent-facing entrypoint for the installable recallloom/ skill package.

Install and trigger this package through your host agent's normal skill discovery flow. RecallLoom itself does not require a custom host-specific launcher inside the package. The package may still ship optional native wrapper templates for supported hosts.

This installable package is intentionally kept lean. Human-facing repository landing pages and marketing docs may exist upstream, but they are not bundled into the installed skill directory.

In the source repository, README.md and README.en.md are concise public front doors, README.zh-CN.md is the compatibility entry, INDEX.md is the full map, and USAGE.md is the operator guide. Those files describe the same helper contract as this installed package entrypoint rather than defining a second logic set.

For package inventory, protocol details, and helper-script behavior, rely on the files that ship inside the package itself:

• managed-assets.json
• package-metadata.json
• references/file-contracts.md
• references/operation-playbooks.md
• references/package-support-policy.md
• references/protocol.md

Package Facts

• package version: 0.4.0
• protocol version: 1.0
• supported protocol versions:
  • 1.0

Runtime Assumptions

• Python 3.10 or newer
• supported workspace languages:
  • en
  • zh-CN
• supported bridge targets:
  • AGENTS.md
  • CLAUDE.md
  • GEMINI.md
  • .github/copilot-instructions.md

Package Support Gate

RecallLoom package support is separate from project sidecar protocol compatibility.

• Helpers MUST perform the package-support check and MUST NOT write support state into project .recallloom/.
• If support is readonly_only, mutating helpers MUST block while diagnostic and read-only helpers MAY continue.
• If support is diagnostic_only, only diagnostic helpers SHOULD continue.
• If support is unknown_offline, diagnostic and read-only actions MAY continue, but mutating actions MUST block until support can be verified.
• Blocked actions MUST return the shared failure contract with blocked_reason: package_support_blocked and a package_support object. See references/package-support-policy.md.

Write Protocol Red Lines

• Managed sidecar writes MUST use helper scripts. Do not bypass them with blind file replacement, blind patching, or hand-built sidecar files.
• Daily-log writes MUST use append_daily_log_entry.py or dispatcher append. Do not handwrite daily-log-entry markers.
• Overwrite-style managed files MUST use revision-aware helper commits. Do not handwrite file-state markers.
• STORAGE_ROOT/state.json and STORAGE_ROOT/config.json MUST NOT be hand-edited during normal operation.
• Protocol 1.0 daily-log counters are file-local: entry-seq is 1..N within one daily log and canonical entry-id is entry-{entry_seq}. Do not treat either as globally unique.
• Keep state.json.daily_logs.entry_count as entry_count; it means the entry marker count in the latest active daily log, not a global cumulative count.
• If a helper write fails, diagnose, fix, retry, then surface the helper failure contract if it still cannot complete.
• Manual repair is allowed only for explicit damaged-sidecar repair; repair marker and state cursor fields as one consistency set, then rerun validate_context.py.

When To Use It

Use RecallLoom when you need to:

• continue an existing project after a pause
• restore project context from maintained files
• maintain current-state project memory
• record meaningful milestone progress
• reduce context drift across sessions or tools

Typical triggers include:

• continue this project
• restore project context
• pick up where we left off
• rl-init
• update the project memory
• record today’s progress
• prepare a clean next-step handoff inside the maintained project files

First Attach Behavior

On first explicit invocation in a project, RecallLoom should not assume the workspace is already initialized.

The correct flow is:

1. detect whether a valid RecallLoom sidecar already exists
2. if it exists, continue normally without making initialization into extra ceremony
3. if it does not exist, explain that the project is not initialized yet and ask whether initialization should be performed
4. if the user explicitly confirms, or directly says rl-init, run the standard initialization action
5. if the environment cannot provide Python 3.10+, stop with a blocked runtime result instead of hand-building a sidecar

rl-init SHOULD mean: initialize the sidecar, validate the workspace, and return next recommended actions. Treat it as a stable high-level action name even when the host does not expose native slash commands.

Current Action Surface

For the current package line, the stable operator-facing wrapper targets are:

• rl-init
• rl-resume
• rl-status
• rl-validate

rl-init is the primary operator-friendly first-attach action name. The others are operator-facing stable action names that can be interpreted by the host agent or mapped into native custom commands when the host supports that surface. rl-bridge remains the canonical dispatcher/helper action label for bridge work, but this package line does not promise a universal native wrapper or deterministic first-hop routing for that label. Natural language remains the default public phrasing for these actions.

The dispatcher command surface also includes quick-summary, append, write, and sync-current-state-after-append. Use quick-summary for current-state snapshots, append --entry-json for milestone logging, write --type ... --source-file <prepared-file> --dry-run or write --type ... --stdin --dry-run before typed managed-file writes, and sync-current-state-after-append --stdin --input-format json only after preflight allows post_append_summary_sync. These dispatcher additions are optional for existing v0.3.4 projects and do not change sidecar protocol 1.0.

Native wrappers for rl-init, rl-resume, rl-status, and rl-validate are convenience entrypoints only. They must delegate to the same dispatcher and must not replace natural-language restore requests, bypass helpers, or create a host-specific product logic copy.

Initialized-Project Restore Contract

When a host or agent sees a generic initialized-project restore request:

1. check for a valid RecallLoom sidecar before broad skill fan-out
2. if the sidecar is valid, route into the normal RecallLoom fast path
3. let broader memory or workflow systems participate only when the sidecar is missing, conflicting, clearly insufficient, or the user explicitly asks for deeper review

For the current package line, rl-resume is the single stable operator-facing action name for that initialized-project restore checkpoint. Natural-language restore requests are still the primary public path. Do not invent a manual sidecar fallback or a host-local restore alias that is not backed by the package contract.

Public Interaction Rules

RecallLoom should default to user task language, not implementation language.

• Prefer “initialize”, “restore”, “import existing project reality”, “continue”, and “record progress”.
• Do not lead with helper names, section keys, or the coldstart label unless the user is explicitly doing operator/debug work.
• Keep the first response result-first and action-light: one clear next move is better than exposing routing details.
• Do not invent a manual sidecar fallback when runtime requirements are missing; surface the blocked state and stop.
• This is not hand-building a sidecar; it is the packaged restore and helper contract.

Fast And Deep Paths

RecallLoom should treat fast path as the default interaction mode.

• Fast path: smallest trustworthy source set, shortest interaction, lowest interruption cost.
• Deep path: only when sources conflict, source coverage is insufficient, risk is too high for a direct recommendation, or the user explicitly asks for deeper review.
• Host-memory inputs remain opt-in and hint-only; their presence should bias the agent toward explicit review instead of silent promotion.

Resume mode selection:

• Use ambient resume or status when the next agent needs the normal tiered read-plan guidance before deciding what to read.
• Use resume --fast when current-state orientation is enough and the next safe move can be chosen from state.json plus rolling_summary.md.
• Use resume --full when stable framing, source-of-truth routing, or project-local update_protocol.md guidance is needed before action.
• Keep daily-log evidence on demand through query_continuity.py; fast and full resume modes should not expand into daily logs by default.

Core File Model

RecallLoom uses three primary memory layers:

• STORAGE_ROOT/context_brief.md: stable project framing
• STORAGE_ROOT/rolling_summary.md: overwrite-style current-state snapshot
• STORAGE_ROOT/daily_logs/YYYY-MM-DD.md: append-only milestone evidence
• STORAGE_ROOT/config.json: machine-readable workspace settings
• STORAGE_ROOT/state.json: machine-readable sidecar state for concurrency-aware helpers
• STORAGE_ROOT/update_protocol.md: recommended project-local override layer for read and write behavior

File responsibilities in one sentence:

• context_brief.md explains what this project is and how it should be approached.
• rolling_summary.md explains what is true right now.
• daily_logs/ explain what happened at milestone level.
• config.json keeps storage and language settings stable.
• state.json tracks workspace revision and helper-visible sidecar state.
• update_protocol.md, when present, can narrow or strengthen the default read/write rules for this specific project.

STORAGE_ROOT is either PROJECT_ROOT/.recallloom/ or PROJECT_ROOT/recallloom/. Exactly one valid storage root MAY exist; if both exist, stop instead of guessing.

Machine-readable markers, not heading labels, are the normative file contract. Protocol 1.0 supports workspace languages en and zh-CN. See references/file-contracts.md.

Minimum Cold-Start Flow

1. Find the project root.
2. Read STORAGE_ROOT/config.json.
3. Read STORAGE_ROOT/state.json.
4. Read STORAGE_ROOT/rolling_summary.md.
5. If STORAGE_ROOT/update_protocol.md exists, surface it before expanding beyond the minimum continuity set.
6. Read STORAGE_ROOT/context_brief.md only when the current task needs framing, scope, source-of-truth, or phase context that the summary does not already cover.
7. Read the latest active daily log only when milestone evidence, workday judgment, or external-writer reconciliation requires it.
8. Run a quick freshness check before trusting older context or before a major write.

Cold start should restore and judge first. It should not automatically continue next_step or execute project work just because continuity files were read.

See references/operation-playbooks.md for the full flow.

Current Read-Side Helpers

Three read-side helpers matter here:

• preflight_context_check.py: revision-aware freshness review before formal writes; returns handoff-first digests, suggested read targets, write-tier guidance, and trust/drift state.
• summarize_continuity_status.py: ambient continuity status surface on the same freshness baseline; returns the same digest family plus shared workday-state and trust/drift guidance.
• query_continuity.py: read-only continuity recall surface; returns answer-first recall with answer, supporting citations, and a risk/freshness note. It also returns hits, token estimate, budget hint, freshness/conflict state, trust/drift state, an output variant label, and override review targets. Daily-log citations include explicit date values, current-state files win ties, and the context window stays bounded.

All attach-safe continuity text returned through these read-side surfaces is expected to respect the shared attached-text scan rules.

Minimum Write Rules

• Before choosing a write target, read STORAGE_ROOT/update_protocol.md if it exists.
• current_state changes usually target rolling_summary.md.
• stable_rule changes usually target context_brief.md.
• milestone_evidence usually targets the daily log.
• Do not update context files for trivial reads or minor edits with no durable change.

Default exits before any write should stay explicit:

• no_write is a normal successful result
• merge_current_state updates rolling_summary.md
• append_milestone appends to the daily log
• confirm and blocked stop automatic writes rather than guessing

Read-side trust notes:

• sidecar_trust_state stays in helper JSON, not in protocol 1.0
• continuity_drift_risk_level is a review signal, not proof that the sidecar is damaged
• allowed_operation_level helps hosts route low-risk read vs review-first vs write-after-preflight flows

Project-local overrides MAY narrow read order, write order, or archive behavior, but they do not replace the core file contract.

Agent Layered Write Judgment

Before writing continuity content, the agent should make the layer decision itself. Helpers can provide safe write context and static write-tier guidance, but they must not replace agent judgment about what the content means.

Use this quick check before editing managed files:

1. Is there a new durable fact, or is no_write the right result?
2. If writing is needed, is the main content stable_rule, current_state, or milestone_evidence?
3. Does the event span multiple layers, so it needs a multi_layer_split?
4. Is the same fact already present, so the right action is merge instead of duplicate?
5. Is the layer uncertain enough to defer or confirm rather than guess?

Layer defaults:

• stable_rule: long-lived workflow rules, source-of-truth routing, project boundaries, or recovery facts. Default target: context_brief.md.
• current_state: what is true now, including current phase, active risks, active judgments, and next steps. Default target: rolling_summary.md.
• milestone_evidence: completed validations, approvals, releases, accepted decisions, or other durable evidence. Default target: daily log.
• no_write, defer, and confirm are valid outcomes when nothing durable changed, the discussion is unstable, or the boundary needs explicit approval.

When more than one layer is valid, split different facts across layers and do not duplicate the same sentence.

For the detailed rules, conflict order, self-review template, and anonymized calibration cases, see references/operation-playbooks.md.

For protocol 1.0, update_protocol.md is a human-reviewed override layer; helpers surface it but do not automatically execute its natural-language rules.

RecallLoom prefers the smallest valid write set. The agent decides what should change and prepares content; helpers decide whether the write is still safe to apply.

When generating workspace files, prefer the user's workspace language when it is supported by protocol 1.0 (en, zh-CN).

When Not To Update Context

Do not update context files just because:

• you performed a cold start
• you answered a short question with no durable project change
• you explored without reaching a stable conclusion
• you made wording-only edits

The protocol is designed to reduce noise, not to turn every session into documentation work.

Profiles

RecallLoom provides four profiles:

• profiles/general-project-continuity.md
• profiles/research-writing.md
• profiles/product-doc-collaboration.md
• profiles/software-project-coordination.md

Profiles refine emphasis, evidence handling, and drift risk. Use general-project-continuity.md by default; switch to a specialized profile only when the project shape is a high-confidence match.

What RecallLoom Does Not Try To Be

RecallLoom does not try to be:

• a general-purpose memory server
• a full agent execution runtime
• a replacement for platform-specific instruction files
• a heavy autonomous coding framework

It is the project continuity layer, not the whole agent stack.

Where To Read More

• references/protocol.md
• references/file-contracts.md
• references/operation-playbooks.md
• references/anti-patterns.md
• references/profiles.md

License

This package is released under Apache License 2.0.