agentleFS
ankit4479ankit4479/outbound-builder-plugin/skills/remember/SKILL.md

remember

Skill0 starsChanged 5 months agoMITView on GitHub

Record or view build-time learnings (error fixes, API quirks, config gotchas) that persist across sessions. Proven patterns are injected at session start.

69 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use agent-context-isolation, agentica-infrastructure and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.

The file

We split this skill into the rules it gives an agent

12 rules. 0 are common, 6 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 61 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If empty or "show" -> View Mode

    line 15
  2. Very specific:

    Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR.

    line 24
  3. Distinctive:

    If the category isn't obvious from the text, make your best judgment.

    line 72
  4. Distinctive:

    Use python3 for deterministic hashing:

    line 81
  5. Very specific:

    Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR.

    line 91
  6. Very specific:

    Check if an entry with the same id already exists:

    line 103
  7. Very specific:

    Write the updated .outbound-builder-plugin-memory.json and confirm:

    line 141
  8. Distinctive:

    If this entry just became proven (success_count went from 1 to 2), highlight it:

    line 150
  9. Distinctive:

    Never record routine operations (successful npm install, normal git commands)

    line 164
  10. Very specific:

    Never record information already documented in imp_doc/

    line 165
  11. Distinctive:

    Keep titles under 80 characters

    line 166
  12. Distinctive:

    Keep descriptions and resolutions to 1-2 sentences each

    line 167

“Common” is measured: kept by at least 6 in 10 of the 61 edited versions of this file we could read. “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

Build-Time Memory

You manage the build-time memory system that captures development learnings and makes future building faster.

Mode Detection

Parse $ARGUMENTS:

  • If empty or "show" -> View Mode
  • Otherwise -> Record Mode (the argument is the learning description)

View Mode

Step 1: Read Memory File

Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR. If it doesn't exist, tell the user:

No build-time memory yet. Learnings are recorded automatically after scaffolding,
or you can record one manually:

  /outbound-builder-plugin:remember "Drizzle push needs SSL disabled for Neon"

Step 2: Present Summary

Display the memory in this format:

Build-Time Memory: <N> entries (<M> proven patterns)

Proven Patterns (applied at session start):
  1. [category] Title -- Resolution
  2. ...

Recent Learnings:
  - [category] Title (success_count: N)
  - ...

Categories: error-fix (<N>), api-quirk (<N>), schema-pattern (<N>),
            config-gotcha (<N>), build-pattern (<N>), domain-insight (<N>)

Show up to 10 recent learnings (sorted by date descending). Show all proven patterns.


Record Mode

Step 1: Parse the Learning

From $ARGUMENTS, determine:

  • category: One of error-fix, api-quirk, schema-pattern, config-gotcha, build-pattern, domain-insight
    • error-fix -- A coding error and what fixed it
    • api-quirk -- Non-obvious API behavior (rate limits, auth, response format)
    • schema-pattern -- Database schema decision or migration insight
    • config-gotcha -- Configuration that's easy to get wrong
    • build-pattern -- Build/deploy/tooling pattern that works well
    • domain-insight -- Domain-specific knowledge about the pipeline's use case
  • title: Short description (under 80 chars)
  • description: What happened (1-2 sentences)
  • resolution: What fixed it or what to do (1-2 sentences)

If the category isn't obvious from the text, make your best judgment. If the description is too vague to extract a useful learning, ask the user to be more specific.

Step 2: Generate Entry ID

The ID is mem- followed by an 8-character slug derived from category + title. This enables deduplication -- the same learning discovered twice gets the same ID.

To generate: take the first 8 alphanumeric characters of a lowercase, hyphenated version of category-title. For example:

  • error-fix + "Drizzle push needs SSL disabled" -> mem-errorfix-

Use python3 for deterministic hashing:

import hashlib
slug = hashlib.md5(f"{category}:{title}".lower().encode()).hexdigest()[:8]
entry_id = f"mem-{slug}"

Step 3: Read or Create Memory File

Read .outbound-builder-plugin-memory.json from $CLAUDE_PROJECT_DIR. If it doesn't exist, initialize:

{
  "version": 1,
  "entries": [],
  "proven_patterns": []
}

Step 4: Dedup and Append

Check if an entry with the same id already exists:

  • If yes: Increment success_count and update date to now
  • If no: Append a new entry:
{
  "id": "<generated-id>",
  "date": "<ISO timestamp>",
  "category": "<category>",
  "title": "<title>",
  "description": "<description>",
  "resolution": "<resolution>",
  "context": {
    "stage": "manual",
    "files": [],
    "tech": [],
    "domain": null
  },
  "success_count": 1,
  "source": "manual"
}

Step 5: Regenerate Proven Patterns

Scan all entries. Any entry with success_count >= 2 becomes a proven pattern. Rebuild the proven_patterns array:

{
  "id": "<entry-id>",
  "category": "<category>",
  "title": "<title>",
  "resolution": "<resolution>"
}

Step 6: Write and Confirm

Write the updated .outbound-builder-plugin-memory.json and confirm:

Recorded: [category] "title"
  -> resolution

(success_count: N, proven: yes/no)

If this entry just became proven (success_count went from 1 to 2), highlight it:

This pattern is now PROVEN and will be injected at session start.

Rules

  • Memory file lives at $CLAUDE_PROJECT_DIR/.outbound-builder-plugin-memory.json
  • IDs are deterministic hashes of category:title -- same learning always gets the same ID
  • Entries with success_count >= 2 are proven patterns
  • Proven patterns are injected by the SessionStart hook at every session start
  • Never record routine operations (successful npm install, normal git commands)
  • Never record information already documented in imp_doc/
  • Keep titles under 80 characters
  • Keep descriptions and resolutions to 1-2 sentences each
  • The memory file should be committed to the repo (it's project knowledge, not secrets)

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.