agentleFS
oleg494oleg494/coding-kit/skills/dev-wiki/SKILL.md

dev-wiki

Skill3 starsChanged 11 days agoMITView on GitHub

Use when prior decisions, project history or preferences could change the answer, or completed work left a durable result: "do you remember", "what did we decide", "save this", "напомни", "запомни", "сохрани". Retrieval with search_all.py and findings.py, plus deterministic save routing — project status to project docs, verified reusable conclusion to findings, portable how-to to the Wiki. Not for current code or fresh research.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Default decision order: already documented by this project → project doc.

    line 31
  2. Very specific:

    Add --verify-cmd "<re-check command>" when the conclusion can be re-checked (findings.py verify <id> runs it), and --supersedes <id> when …

    line 47
  3. Very specific:

    Keep a handoff compact: the command run, the state/scope/environment, the result, and what invalidates it (a change, a failure, an …

    line 138

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Dev Wiki — cross-session developer memory

Memory root: MEMORY_ROOT, otherwise ~/.memory. Each record has exactly one home; a second copy adds drift, not redundancy.

Precedence

  • A read-only, review-only or plan-only scope, "do not save" / "не сохраняй", and stop suppress automatic saves. An explicit save request in that same turn is still honored for the named record only — no cleanup sweep follows.
  • A newer correction supersedes the record it corrects.
  • A retrieval- or review-only task rebuilds no index. Only an authorized source change refreshes the index that covers it.

Routing: one home per record

ContentHomeIndex refresh
Project-specific status, config, or a decision this project already documentsthe existing project doc (docs/, an ADR, WORK/<project>/docs/) — edit that section in placeonly an index that already covers the changed doc
A verified, reusable conclusion about a problem or topicfindings store (research.db)none
A portable how-to, reference, error lesson or decision~/.memory/Wiki/<type>/<slug>.mdWiki cycle below

Default decision order: already documented by this project → project doc; a conclusion with a source → finding; portable knowledge → Wiki file. Knowledge that lives and dies with the project stays in the project; anything reusable across projects goes to the global store.

Save

Finding — search first, then update rather than duplicate:

python ~/.memory/db-tools/findings.py search "distinctive token"
python ~/.memory/db-tools/findings.py add "<topic>" --text "<conclusion>" --source <path or URL> --project <slug> --importance <high|normal|low>
python ~/.memory/db-tools/findings.py edit <id> --project <slug> --importance <level>
python ~/.memory/db-tools/findings.py show <id>

Add --verify-cmd "<re-check command>" when the conclusion can be re-checked (findings.py verify <id> runs it), and --supersedes <id> when it replaces older records.

Wiki file — new file or in-place update of ~/.memory/Wiki/<type>/<slug>.md:

---
type: reference
title: "Title"
description: "What it covers"
date: 2026-08-15
tags: [category, topic]
origin: web                             # web | session | subagent | manual
source_url: https://example.com/page    # required when origin is web
---

origin records where the content came from: web (fetched by read or browser), session (this conversation), subagent (delegated output) or manual (stated by the user). origin: web requires source_url:. lint_wiki.py checks both: a missing origin is a WARN (legacy notes predate the rule); origin: web without source_url: is an error and exits 1.

Then add the entry to ~/.memory/Wiki/index.md, append a line to ~/.memory/Wiki/log.md, and complete the cycle:

python ~/.memory/db-tools/build.py
python ~/.memory/db-tools/lint_wiki.py   # exit 1 on errors; fix before reporting the save

Project doc — edit the existing section; rebuild only an index that already indexes that document: python ~/.memory/db-tools/build.py -r <root> -o ~/.memory/db/<name>.db.

Record types (global Wiki)

TypeFolderContent
referenceWiki/reference/Fact, documentation
howtoWiki/howto/Instruction, guide
errorWiki/errors/Bug, incident, lesson
decisionWiki/decisions/ADR, architectural decision
ideaWiki/ideas/Idea, not yet a decision

Findings metadata

Projects are discovered from ~/.memory/db/*.db plus optional projects.json; slug format [a-z0-9][a-z0-9_-]{0,63}. Reserved slugs: portable for cross-project techniques and tools, unknown for notes not tied to a project.

Importance drives retrieval filters: high invariants, security boundaries and data-loss prevention; normal actionable engineering findings, runbooks, setups; low checkpoints and scratch notes; unreviewed the default before review. Batch classification is atomic and idempotent, and preserves user-curated records (cli_edit provenance) unless --force is passed:

python ~/.memory/db-tools/findings.py classify mapping.json --dry-run
python ~/.memory/db-tools/findings.py classify mapping.json

Retrieve

python ~/.memory/db-tools/search_all.py "distinctive token"                    # every store at once
python ~/.memory/db-tools/search_all.py "token" --project <slug> --importance high
python ~/.memory/db-tools/search_all.py "token" --project portable             # reusable patterns only
python ~/.memory/db-tools/search_all.py "token" --substring                    # declensions, partial words
python ~/.memory/db-tools/search_all.py "token" --state current --verification verified
  • Lexical FTS5 is the default: space-separated terms must all match. Start from a distinctive project or component token, not a full sentence; widen only after seeing what the first pass returned.
  • --mode vector or hybrid requires an explicitly built local ONNX index (--model-dir, see the README). Never silently substitute lexical hashes or a hosted embedding API.
  • --state superseded inspects replaced records; --verification unverified isolates unproven ones. Project and importance filters apply before limits.
  • A hit is a snippet, not the decision: open findings.py show <id> or the source file before relying on it.
  • Lifecycle badges: [superseded by #N] — resolve to the replacement before use; [unverified] — treat as unconfirmed.
  • Empty result: try a materially better token or a supported OR, then report what was searched. No hits in scope does not prove that no policy exists.
  • Composition: to keep portable patterns available while scoping to a project, query --project <slug> and --project portable, or query globally.

memory/scripts/memory-warmup.py (diagnostic; --full for the complete feed) ranks high/normal unanchored items above checkpoints and shows each active invariant's verification status.

Handoff records

Keep a handoff compact: the command run, the state/scope/environment, the result, and what invalidates it (a change, a failure, an unresolved concern). Reuse it while that state is unchanged instead of building a tracking subsystem around it.

Tag vocabulary: architecture, engineering, security, performance, devops, testing, frontend, backend, database, api.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.