# Prompt Corpus > Turn a transcript history into a queryable record of decisions — raw prompts, one judgement per prompt, and views that answer "what is still binding", "what did I say that nobody acted on", and "what did I ask that was never answered". Use when adding new prompts to the corpus, when re-running the judging pass, or when answering a question about what the operator has already decided. - Skill: `jonhill90/prompt-corpus` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add jonhill90/prompt-corpus` - Raw SKILL.md: https://api.skillmd.com/api/skills/jonhill90/prompt-corpus/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: jonhill90 (https://skillmd.com/u/jonhill90) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/jonhill90/prompt-corpus --- # Prompt corpus A chat archive answers *what did I say*. This answers *what is still binding, what did nobody act on, and what did I ask that was never answered* — which is a different thing and needs a different shape. The whole design rests on one boundary: **a model runs ONCE per prompt, at write time. Every read afterwards is plain SQL.** Break that and this becomes another thing that needs inference to answer a question, which is what it exists to replace. ## The layers ``` prompts raw + cleaned + context + project. text_raw is IMMUTABLE. items one judgement per row: kind, body, weight, status, resolved_to links conflicts_with / supersedes / depends_on — recorded by hand, NEVER inferred views unacknowledged · live_parameters · open_questions · conflicts · possibility_count ``` `context` is `NOT NULL` and it is load-bearing, not decoration. "Live." means nothing without knowing it answered "live terminal or refreshed preview?". ## The pipeline ```bash itemize_prompts.py --extract [--limit N] # pure SQL, decides nothing # the ONE model step itemize_prompts.py --load judged.json # pure SQL, idempotent by hashed id ``` Item ids derive from `(prompt_id, index, body)`, so re-loading the same judgements writes 0. Always verify that after a load — an idempotency claim nobody tested is not a property. At scale, run the judging as a dynamic workflow: `.claude/workflows/corpus-itemise.js` on the `feat/prompt-corpus-skill` branch of `agent-supervisor` (could not measure whether this has since merged to `main`). Agents judge and write JSON **only**; a single serial agent does every ledger write. Twelve concurrent writers on one SQLite file contend. ## The judging rules — these are the technique Get these wrong and the corpus is worse than nothing, because it will look authoritative while being wrong. - **Every prompt gets an entry.** A prompt worth nothing durable gets ONE item with `kind=thought`, `weight=retracted`, `status=dropped` and a `status_reason`. Never omit one: `--extract` selects prompts with no `items` row, so an omitted prompt resurfaces at the head of every future batch, forever. This is the single most common mistake and two independent agents made it before it was written down. - **`resolved_to` is only for things that CONSTRAIN** — `tooling=cli_first`, `ui_fidelity=1:1`. A question or a one-off directive has no `resolved_to`. - **`weight=hard` means binding; `preference` means he leans that way.** Getting this wrong manufactures false conflicts. A preference was once treated as binding and cost a whole session. - **Do not soften tone.** If he was blunt, the body stays blunt. You are recording what he meant, not making it polite. - **Do not invent context.** If a prompt is ambiguous, say so in the body rather than guessing a meaning. - **Noise is DROPPED WITH A REASON, never deleted.** An exclusion must be reviewable and reversible. ## Noise: structural markers only, never topic keywords Matched literally, no model: ``` "do exactly what it says" "That file is your complete brief" "carry it out exactly as written" "Base directory for this skill:" "## Context Usage" "Supervisor loop tick" "" ``` **A topic-keyword filter is a trap.** Filtering on `career`/`resume` matched `Hill90 resume sweep` and several real PR discussions. Structure is a property of who wrote the text; topic is not. ## Traps, each of which cost real time - **Do not sample with `order by length(text_raw) desc`.** It selects FOR machine text and produced a confident wrong conclusion that the corpus was mostly junk when 50 rows were. - **Project provenance is not in `source_file`** — that is only a session UUID. Recover it from the transcript's directory under `~/.claude/projects/`, or capture it at write time from the hook's `cwd`. - **The loader is not atomic.** It writes item-by-item with no transaction, so one malformed item leaves a partial write. Check what actually landed before re-running; ids are deterministic so a corrected re-run fills only the gap. - **`kind` and `weight` are different axes.** `preference` is a WEIGHT. A judge emitting `kind: preference` is a schema error, not a judgement. - **A missing `body` crashes the loader** with `KeyError`. Validate the judged file before loading it. ## Reading it ```sql select count from possibility_count; -- how many hard constraints are live select * from unacknowledged; -- said, never acted on select * from open_questions; -- asked, never answered select * from live_parameters where weight='hard'; ``` `conflicts` reports links someone recorded. It never infers one — deciding two items genuinely contradict, rather than describing different scopes or one superseding the other, is judgement and stays with something accountable. ## Before you answer a question about what the operator decided **Query the corpus first.** That is what it is for, and forgetting to is the most likely way this skill goes unused: the answer to "should we build X first" is usually already in `live_parameters`, in his own words, with more authority than a fresh opinion.