Agent skill

Promote Memory

by pedrohcgs in pedrohcgs/claude-code-my-workflow

Review candidate learnings in Claude Code's native auto memory (~/.claude/projects/<project/memory/, machine-local) and run them through a five-critic council in parallel: generality, staleness…

MITAuto-check passedAgent Workflows

Install Promote Memory

skills CLI
$ npx skills add pedrohcgs/claude-code-my-workflow --skill promote-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install pedrohcgs/claude-code-my-workflow promote-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/promote-memory .claude/skills/promote-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
promote-memory
GitHub stars
1.7k
Token cost
~3k tokens
SKILL.md length
847 words
Files
1
Skills in repo
59
Repo updated
First seen
Licence
MIT

At a glance

Review candidate learnings in Claude Code's native auto memory (~/.claude/projects/<project/memory/, machine-local) and run them through a five-critic council in parallel: generality, staleness…

  • Works in 9 steps: Generality critic → Staleness critic → Redundancy critic → …
  • User says promote memory
  • SKILL.md covers When to use, When NOT to use, The five critics and Steps
  • Calls claude

What it does

Promote Memory is an agent skill from pedrohcgs/claude-code-my-workflow. Review candidate learnings in Claude Code's native auto memory (~/.claude/projects/<project/memory/, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format. Majority vote (3+ of 5) promotes the entry to MEMORY.md. Use when user says "promote memory", "review my learnings", "what should graduate to MEMORY.md", "five-critic council", or as monthly memory maintenance.

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent memory. The repository describes itself as: A ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols. The licence is MIT.

When your agent uses it

  • User says promote memory
  • Review my learnings
  • What should graduate to MEMORY.md
  • Five-critic council

Example prompts

  • “promote memory”
  • “review my learnings”
  • “what should graduate to MEMORY.md”
  • “/promote-memory”

Requirements

  • Pre-approved tools (allowed-tools): ["Read", "Write", "Glob", "Grep", "Agent", "Task", "Bash"]

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Generality critic
  2. Staleness critic
  3. Redundancy critic
  4. Evidence critic
  5. Format critic
  6. Read candidate entries
  7. Spawn the council
  8. Aggregate votes
  9. Present the verdicts

What it can do on your machine

Read from SKILL.md and the folder at commit ae72617. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • ["Read"
    • "Write"
    • "Glob"
    • "Grep"
    • "Agent"
    • "Task"
    • "Bash"]

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • claude

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Promote Memory loads about 3k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 847 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~113
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from pedrohcgs/claude-code-my-workflow at commit ae72617, republished under its MIT licence (© pedrohcgs). 847 words, ~2,978 tokens.

Download SKILL.mdSave it as .claude/skills/promote-memory/SKILL.md (or your agent's skills folder).
name
promote-memory
description
Review candidate learnings in Claude Code's native auto memory (`~/.claude/projects/<project>/memory/`, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format. Majority vote (3+ of 5) promotes the entry to MEMORY.md. Use when user says "promote memory", "review my learnings", "what should graduate to MEMORY.md", "five-critic council", or as monthly memory maintenance.
allowed-tools
["Read", "Write", "Glob", "Grep", "Agent", "Task", "Bash"]
argument-hint
[entry-substring or 'all']
disable-model-invocation
true
metadata
author: Claude Code Academic Workflow version: 1.0.0
<!-- Pattern adapted with attribution from Chris Blattman's claudeblattman v2.1
     "Five-critic council" (claudeblattman.com, Apr 2026 continuous-improvement
     loop). Blattman uses it to decide what enters his MEMORY layer; we adapt
     it to the auto-memory → MEMORY.md promotion question codified in
     .claude/rules/meta-governance.md. -->

/promote-memory — five-critic council for memory promotion

The template's meta-governance.md rule splits memory into two tiers:

  • MEMORY.md (committed, ≤ 200 lines) — generic learnings that help all forkers.
  • native auto memory (~/.claude/projects/<project>/memory/ — machine-local, typed user/feedback/project/reference, no size cap on topic files) — machine-specific and user-specific learnings.

The rule says generic patterns should sync via git; personal patterns stay local. What it doesn't say is who decides which is which. /promote-memory operationalizes the call: spawn five critics in parallel, each reviewing the candidate [LEARN] entries on a single dimension, and promote on majority vote (3+ of 5).

When to use

  • Monthly memory maintenance. Personal-memory accumulates faster than MEMORY.md; the council periodically harvests the genuinely generic learnings.
  • Before sharing a fork. Someone is about to clone your template — what should they inherit?
  • After a large project ships. Lessons from a paper or a course cycle deserve curation before the next project starts adding noise.
  • Not on a schedule. This skill is user-invoked (disable-model-invocation), so a scheduled task cannot fire it, and its candidates live in machine-local auto memory that a cloud routine cannot see. Set yourself a monthly reminder and run it in a local session; every promotion waits for your approval anyway.

When NOT to use

  • For a single fresh [LEARN] after a single correction. Just let auto memory record it; let it sit until the next council runs.
  • For deleting stale entries. Edit MEMORY.md by hand, per meta-governance.md (dated addendum, or a merge to hold the cap). /promote-memory never deletes — though near the cap it proposes a demotion (Step 4).
  • For project-specific context. That belongs in CLAUDE.md or session logs, not in either memory tier.

The five critics

Each critic runs in an isolated, fresh context (its own Agent call — never a conversation fork) — they don't see each other's verdicts or the user's draft. Each casts one YES/NO vote per candidate entry with a one-sentence rationale.

1. Generality critic

"Would a non-econ forker benefit from this [LEARN] entry — a biology PhD, a sociology postdoc, a CS instructor? If the lesson is specific to your setup (your bibliography path, your machine's TeX install, your discipline's notation), vote NO."

2. Staleness critic

"Does this entry contradict the current state of the codebase? Run grep -r on the file paths, function names, or settings the entry references. If the referenced thing has been renamed, removed, or significantly changed, vote NO — the entry is stale and would mislead a future session."

3. Redundancy critic

"Is this lesson already encoded in MEMORY.md, CLAUDE.md, or an existing rule? Read the relevant files. If yes (even paraphrased), vote NO — duplication erodes the index's signal."

4. Evidence critic

"Does the entry cite the incident, file path, or specific case that motivated it? If the entry is [LEARN:foo] always do X with no anchor to why, vote NO. Future Claude can't judge edge cases without the rationale."

Show full SKILL.md (373 more words)Show less
5. Format critic

"Does the entry fit the format of the tier it lands in? MEMORY.md entries are [LEARN:category] wrong → right (see MEMORY.md itself); a feedback/project candidate coming from native auto memory should carry the **Why:** + **How to apply:** lines auto memory writes, so the reason survives the move. If it's just a free-form note, vote NO — fix the format first, then re-submit."

Council verdict

Each critic returns YES/NO + rationale. The promotion threshold is majority (3+ YES).

  • 5 YES — promote without modification.
  • 4 YES — promote with a one-line note about the dissenting concern.
  • 3 YES — promote but address the dissenting critics' concerns first (typically: trim, add evidence, fix format).
  • 2 or fewer YES — do not promote. Either fix the entry per the dissenting critics' feedback and re-submit, or leave it in auto memory.

Steps

Step 1: Read candidate entries

If $ARGUMENTS is all, read every topic file in ~/.claude/projects/<project>/memory/ (skip the MEMORY.md there: it is only an index pointing at the topic files); each topic file is one candidate. Otherwise treat $ARGUMENTS as a substring filter on a topic file's filename, description, or type (e.g., latex matches feedback_latex_texinputs.md, and feedback matches every feedback memory). Auto memory does not store entries in [LEARN:category] form; a candidate is rewritten into that shape only for the proposal in Step 4.

Step 2: Spawn the council

Five Agent invocations in parallel, one per critic, each in a fresh context:

  • Generality critic — context: the candidate entry + a one-paragraph description of who the template's audience is (academic researchers across disciplines).
  • Staleness critic — context: the candidate entry + the ability to Read / Grep the codebase. Should explicitly check any file paths / function names / settings the entry references.
  • Redundancy critic — context: the candidate entry + the current MEMORY.md + CLAUDE.md + relevant rule files.
  • Evidence critic — context: the candidate entry only. Vote based on whether the entry self-describes its motivation.
  • Format critic — context: the candidate entry + .claude/rules/meta-governance.md for the schema reference.

Use the Haiku tier for all five critics (per .claude/rules/model-routing.md: mechanical-ish review work). The user can override via the agent's model: field if they want Sonnet for the harder calls.

Step 3: Aggregate votes

Collect verdicts. For each candidate entry, compute the vote count + per-critic verdicts.

Step 4: Present the verdicts

For each entry:

markdown
## `[LEARN:foo] <summary>`

**Vote:** 4-of-5 YES (promote with note)

| Critic | Vote | Rationale |
|---|:---:|---|
| Generality | YES | ... |
| Staleness | YES | ... |
| Redundancy | YES | ... |
| Evidence | NO  | Entry doesn't cite the originating incident. Add a one-line "Incident:" pointer before promoting. |
| Format | YES | ... |

**Recommendation:** Address Evidence critic, then promote.

**Proposed MEMORY.md addition:**
```text
[LEARN:foo] <full proposed text>

**Near the cap, adding means removing.** MEMORY.md is capped at 200 lines **and** 25KB, and the byte cap usually binds first. When the file plus the proposed additions would pass ~190 lines or ~24KB (`wc -c MEMORY.md`), the report also names the **weakest current entry** as a demotion candidate — stale (a named file, flag, or model that no longer exists), contradicted by a newer rule, or local rather than generic — with the evidence, and asks the user whether to move it to auto memory or delete it. The test for keeping an entry: *would removing it cause a mistake on many tasks?*

### Step 5: User approves the promotions

The user reviews the report and explicitly approves which entries to promote. The skill writes approved entries to MEMORY.md, marks the same entries in their auto-memory topic files with `# promoted YYYY-MM-DD` for audit, and surfaces a summary.

Do **not** auto-promote — even on 5-of-5 YES votes. The user's approval is the final gate.

## Output

- Per-entry council report (verdicts, rationales, recommendations) — to the conversation.
- On approval: MEMORY.md updated (append at appropriate `[LEARN:category]` section), the auto-memory topic file updated (entry marked promoted).
- A `quality_reports/memory_promotion_<date>.md` audit file recording the full council session for forensics.

## Anti-patterns

- **Auto-promoting on 5-of-5 YES.** Even unanimous critic agreement can be wrong; the user's domain judgment is the final gate.
- **Re-running the council on the same entry repeatedly** hoping for a different result. If 4 critics consistently say NO, the entry doesn't belong in MEMORY.md — leave it in auto memory and stop.
- **Skipping the Evidence critic** because the entry "looks obvious." Evidence is what makes the entry portable across forkers; obvious-to-you ≠ obvious-to-them.
- **Demoting via this skill.** It only promotes. Demotion is a manual edit + commit.

## Cross-references

- [`.claude/rules/meta-governance.md`](../../rules/meta-governance.md) — the two-tier memory contract this skill operationalizes.
- [`.claude/agents/promote-memory-council.md`](../../agents/promote-memory-council.md) — the five-critic implementation (one agent file with five role specs, dispatched in parallel via the `Agent` tool).
- [`.claude/rules/model-routing.md`](../../rules/model-routing.md) — why critics default to Haiku tier.
- `/learn` (existing skill) — captures new `[LEARN]` entries; pairs with `/promote-memory` (which decides what graduates).

## Source of candidates (v2.5)

Candidates come from **native auto memory** — `~/.claude/projects/<project>/memory/`. Claude
writes these itself as it works, typed `user` / `feedback` / `project` / `reference`, and the
`MEMORY.md` there is an index, not the content.

The promotion question is unchanged and is the whole point: *would a researcher in a different
field, forking this template, be better off knowing this?* If yes it belongs in the committed
`MEMORY.md`; if it is about this machine, this dataset, or this person's preferences, it stays
local.

**Retired:** `.claude/state/personal-memory.md`. The two-tier idea was right; Claude Code now
ships the local tier natively, so the hand-rolled file is redundant. An existing one still
reads as a plain file, but nothing writes to it.

## The capture gate — before anything is remembered

Promotion decides what becomes *shared* knowledge. This gate decides what is worth recording
**at all**. Five questions; a candidate must pass all five:

1. **Durable** — will this still be true in six months, or is it about today's branch?
2. **Non-obvious** — would a competent person rediscover it in five minutes anyway?
3. **Stable** — does it describe a rule, or a symptom that a fix will erase?
4. **Specific** — is it actionable, or is it a mood? *"Be careful with merges"* is a mood.
5. **Not already captured** — does an existing entry cover it? Extend that one instead.

> **Just-in-case memories are banned.** They pollute the index and make the useful entries
> unfindable. A memory store nobody trusts is a memory store nobody reads.

Promotion from local observation to committed knowledge is a **reviewed act, not an autosave** —
which is why the five-critic council exists and why the user is the final gate even on a
unanimous vote.

© pedrohcgs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/promote-memory of pedrohcgs/claude-code-my-workflow.

Open the folder on GitHubat commit ae72617

Compare with similar skills

Promote Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Promote Memory compared with similar skills
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Promote Memory this skillpedrohcgs/claude-code-my-workflow1.7k—~3kAutomated safety check: PassMIT
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Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Reflect on Session Learningscursor/plugins11k5 repos~1.2kAutomated safety check: PassNone
MemPalace Memory SearchMemPalace/mempalace59k—~1.4kAutomated safety check: PassMIT
Compound Learning WriterEveryInc/compound-engineering-plugin25k—~2kAutomated safety check: PassMIT

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Categories

Questions about Promote Memory

What does Promote Memory do?

Review candidate learnings in Claude Code's native auto memory (~/.claude/projects/<project/memory/, machine-local) and run them through a five-critic council in parallel: generality, staleness…. Promote Memory is an agent skill from pedrohcgs/claude-code-my-workflow.claude/projects/<project/memory/, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format.

When should I use Promote Memory?

Promote Memory fits situations like: user says promote memory; review my learnings; what should graduate to MEMORY.md; five-critic council.

How do I install Promote Memory in Claude Code?

Run `npx skills add pedrohcgs/claude-code-my-workflow --skill promote-memory -a claude-code`. Or copy the skill folder (.claude/skills/promote-memory in pedrohcgs/claude-code-my-workflow) into .claude/skills/promote-memory in your project. Claude Code loads it when a task matches its description.

How do I install Promote Memory in Codex?

Run `npx skills add pedrohcgs/claude-code-my-workflow --skill promote-memory -a codex`. Or copy the skill folder (.claude/skills/promote-memory in pedrohcgs/claude-code-my-workflow) into .agents/skills/promote-memory in your project. Codex loads it when a task matches its description.

Can I use Promote Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pedrohcgs/claude-code-my-workflow --skill promote-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/promote-memory, .gemini/skills/promote-memory, .github/skills/promote-memory and .opencode/skills/promote-memory in your project.

What does Promote Memory need to run?

Going by SKILL.md and its folder, Promote Memory needs the command-line tools its instructions call (claude). Its frontmatter pre-approves these tools: ["Read", "Write", "Glob", "Grep", "Agent", "Task", "Bash"].

Does Promote Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Promote Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Promote Memory use?

Promote Memory is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Promote Memory use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Promote Memory?

Skills that share tags, products or a category with Promote Memory: Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), Beads Task Memory (gastownhall/beads, 28k stars), Reflect on Session Learnings (cursor/plugins, 11k stars) and MemPalace Memory Search (MemPalace/mempalace, 59k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Promote Memory?

pedrohcgs (a GitHub user) maintains it in pedrohcgs/claude-code-my-workflow, which has 1,655 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on September 27, 2026.

Source: pedrohcgs/claude-code-my-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.