Agent skill

Professional Brain

by mohitagw15856 in mohitagw15856/pm-claude-skills

Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to.

MITAuto-check passed

Install Professional Brain

skills CLI
$ npx skills add mohitagw15856/pm-claude-skills --skill professional-brain -a claude-code

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

GitHub CLI
$ gh skill install mohitagw15856/pm-claude-skills professional-brain --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/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/professional-brain .claude/skills/professional-brain && 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
professional-brain
GitHub stars
1.4k
Token cost
~2.2k tokens
SKILL.md length
982 words
Files
3 (incl. scripts)
Skills in repo
1,348
Repo updated
First seen
Licence
MIT

At a glance

Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to.

  • Works in 3 steps: Propose — show the records you'd write… → Approve — the user confirms, edits, or… → Append — write the approved records with…
  • Asked to set up a brain
  • SKILL.md covers What This Skill Produces, Required Inputs, The Brain Schema and Provenance Tags (the trust…, plus 7 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Professional Brain is an agent skill from mohitagw15856/pm-claude-skills. Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to. Use when asked to set up a brain, ingest notes/artifacts into memory, recall what's known about a topic, log a decision with provenance, or run a weekly brain review. Produces a structured brain/ folder (knowledge, decisions, hypotheses, stakeholders, entities, source) with provenance-tagged facts, plus ingest/recall/record/review operations with…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/brain_query.py` and `scripts/brain_write.py`).

The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.

When your agent uses it

  • Asked to set up a brain
  • Ingest notes/artifacts into memory
  • Recall whats known about a topic
  • Log a decision with provenance

Example prompts

  • “/professional-brain”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Propose — show the records you'd write (section · tag · text). Preview with
  2. Approve — the user confirms, edits, or drops items. Never write without a yes.
  3. Append — write the approved records with --commit. Append-only: decisions become a new

What it can do on your machine

Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Professional Brain loads about 2.2k tokens when it runs. Until then it costs about 143 tokens; SKILL.md has 982 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~143
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 982 words, ~2,215 tokens.

Download SKILL.mdSave it as .claude/skills/professional-brain/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
professional-brain
description
Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to. Use when asked to set up a brain, ingest notes/artifacts into memory, recall what's known about a topic, log a decision with provenance, or run a weekly brain review. Produces a structured brain/ folder (knowledge, decisions, hypotheses, stakeholders, entities, source) with provenance-tagged facts, plus ingest/recall/record/review operations with approval-gated, append-only write-back.

Professional Brain Skill

🚀 New to this? Start with the 5-minute Quickstart — a folder + one file, with a worked example. This file is the full reference.

Most skills start cold — you paste the same context every time, and decisions made six weeks ago lose the why. This skill gives the library a memory: a plain-markdown brain/ folder on disk that skills read before they answer and write to after. No vector DB, no cloud — just grep-able files you (and Claude) can audit and edit.

This is the state layer of an AI teammate. Pair it with the action layer (skills that file tickets / open PRs) and you get a loop: recall → do the work → record the decision → review.

What This Skill Produces

  • A scaffolded brain/ folder with a fixed schema (see below).
  • Provenance-tagged knowledge — every claim says where it came from and how strong it is.
  • Four operations you can invoke: init, ingest, recall, review.
  • A standing contract other skills follow: read the relevant brain files first; write durable outcomes (decisions, new facts, stakeholder asks) back.

Required Inputs

Ask for these only if they aren't already on disk or in the request:

  • Which operation — init, ingest, recall, or review (default: infer from the ask).
  • For ingest: the artifact (a pasted note, a file path, a transcript) and what it's about.
  • For recall: the topic or question to answer from memory.
  • The brain location — default ./brain/ at the project root.

The Brain Schema

brain/
  context.md      # who/what: product, ICP, metrics definitions, voice (supersedes pm-context.md)
  knowledge/      # durable facts — strategy.md, market.md, users.md, org.md
  decisions/      # one file per decision: what, why, alternatives rejected, reopen-when
  hypotheses/     # assumptions: statement, evidence, status (open/validated/invalidated)
  stakeholders/   # one file per person: asks, concerns, comms history
  entities/       # typed objects: features, accounts, experiments — the artifact graph
  source/         # immutable originals (audit trail) — never edited after capture

It is Obsidian-vault compatible: open brain/ as a vault and the links become a graph.

Provenance Tags (the trust mechanism)

Every fact carries a tag in square brackets so its strength is explicit. Skills must keep the tag when they reuse a fact, and downgrade confidence for weak tags.

TagMeansStrength
[data]from analytics / a metric / a measured resultstrong
[interview]from a documented user or customer interviewstrong
[external]from third-party / market researchmedium
[verbal]said in a meeting, not independently documentedweak
[hunch]informed intuition, no evidence yetweakest

Example: Mobile drives 65% of DAU [data]. Enterprise wants SSO before renewing [verbal].

Operations

init — Create the folder schema. Migrate an existing pm-context.md into context.md. Offer to ingest any artifacts the user already has (Notion export, Jira CSV, notes).

ingest <thing> — Store the original verbatim in source/, then synthesise it into the right durable file(s) (knowledge/, decisions/, hypotheses/, stakeholders/), tagging each extracted claim with its provenance. Never discard the source.

recall <query> — Answer from memory. Use the helper script to find matching facts across the brain, then synthesise an answer that cites each fact's file and tag. If memory is thin, say so rather than inventing.

record — The write-back half of the loop (Phase 1). After a skill produces an artifact (or on demand), extract the durable outcomes worth remembering — decisions made, new facts learned, assumptions surfaced, stakeholder asks — and propose them as a numbered list, each with its target section and provenance tag. This is the action surface, so it is approval-gated and dry-run by default:

  1. Propose — show the records you'd write (section · tag · text). Preview with brain_write.py … (no --commit), which prints exactly what would be appended.
  2. Approve — the user confirms, edits, or drops items. Never write without a yes.
  3. Append — write the approved records with --commit. Append-only: decisions become a new numbered file; everything else appends to its named file. Nothing is overwritten.

Downgrade weak evidence honestly — a conclusion from one call is [interview], a gut call is [hunch]; don't launder it into [data].

review — Weekly sweep. Flag: stale hypotheses (open too long with no new evidence), decisions whose reopen-when condition now holds, contradictions between files, and facts that are only [hunch]/[verbal] but are being treated as settled. Draft the updates; don't apply silently.

Show full SKILL.md (360 more words)Show less

Programmatic Helper

scripts/brain_query.py (stdlib only) does deterministic recall — it greps the brain for a query and returns matches with their file and detected provenance tag, so retrieval is transparent (no embeddings, no guessing).

bash
# Find what the brain knows about "activation", newest-first, as text
python3 scripts/brain_query.py ./brain "activation"

# JSON for chaining into another step
python3 scripts/brain_query.py ./brain "enterprise SSO" --json

Use its output as the grounded evidence set, then synthesise the answer on top — never answer a recall from outside the brain without saying so.

scripts/brain_write.py is the write-back counterpart — it appends a provenance-tagged record (append-only, never overwrites) and is dry-run by default so you can preview before committing:

bash
# Preview what would be written (changes nothing):
python3 scripts/brain_write.py ./brain decisions "Prioritise mobile" --tag data --body "68% of churn is mobile" --source "Q3 analytics"

# Write it after approval:
python3 scripts/brain_write.py ./brain decisions "Prioritise mobile" --tag data --body "…" --source "Q3 analytics" --commit

The contract for other skills

A brain-aware skill adds a short "Reads from / Writes to the Brain" section:

  • Reads: before producing, pull the relevant files (e.g. prd-template reads context.md, knowledge/strategy.md, and any related hypotheses/ + entities/).
  • Writes: after producing, append durable outcomes (e.g. meeting-notes writes each decision to decisions/, new asks to the relevant stakeholders/ file), each provenance-tagged.

Output Format

For ingest, confirm what was captured:

Ingested: [artifact]
  • Source saved: source/[file]
  • Knowledge updated: knowledge/[file] — [facts added, each tagged]
  • Decisions logged: decisions/[id] — [if any]
  • Hypotheses touched: [statement → status]
  • Open follow-ups: [anything needing a human]

For recall, answer then show your grounding:

Recall: [query]

[Synthesised answer.]

Grounded in:

  • decisions/0003-...md — "..." [data]
  • stakeholders/sarah.md — "..." [verbal]

Quality Checks

  • Every extracted claim carries a provenance tag
  • The verbatim original is saved in source/ before synthesis
  • Recall answers cite the file + tag for each fact, and flag thin memory instead of inventing
  • Decisions record the rejected alternatives and a reopen-when condition
  • [hunch]/[verbal] facts are never presented with the confidence of [data]/[interview]

Anti-Patterns

  • Do not paraphrase a source into the durable layer without keeping the original in source/ — the audit trail is the point
  • Do not drop provenance tags when reusing a fact — an untagged claim is an unfalsifiable one
  • Do not answer a recall from general knowledge and present it as something the brain "knows" — say when memory is empty
  • Do not overwrite a decision when it changes — append a new dated entry so the history survives
  • Do not build a vector database or hide memory behind embeddings — the brain stays plain, grep-able markdown a human can read and correct

Example Trigger Phrases

  • "Set up a brain."
  • "Log a decision with provenance."
  • "Run a weekly brain review."

© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in skills/professional-brain of mohitagw15856/pm-claude-skills.

  • SKILL.md
  • scripts/brain_query.py
  • scripts/brain_write.py

Open the folder on GitHubat commit 1cbf1f0

Compare with similar skills

Professional Brain 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.

Professional Brain compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Professional Brain this skillmohitagw15856/pm-claude-skills1.4k—~2.2kAutomated safety check: PassMIT
Wiki Maintaineropenclaw/openclaw392k1 repos~462Automated safety check: PassMIT
Obsidian Vault Maintaineropenclaw/openclaw392k1 repos~262Automated safety check: PassMIT
Openclaw PR Maintaineropenclaw/openclaw392k—~2.3kAutomated safety check: PassMIT
Brainjeremylongshore/tons-of-skills-marketplace2.8k—~1.9kAutomated safety check: PassApache-2.0
Open Source Maintainer Assistantslopus/happy24k—~1.9kAutomated safety check: PassMIT

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Questions about Professional Brain

What does Professional Brain do?

Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to. Professional Brain is an agent skill from mohitagw15856/pm-claude-skills. Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to.

When should I use Professional Brain?

Professional Brain fits situations like: asked to set up a brain; ingest notes/artifacts into memory; recall whats known about a topic; log a decision with provenance.

How do I install Professional Brain in Claude Code?

Run `npx skills add mohitagw15856/pm-claude-skills --skill professional-brain -a claude-code`. Or copy the skill folder (skills/professional-brain in mohitagw15856/pm-claude-skills) into .claude/skills/professional-brain in your project. Claude Code loads it when a task matches its description.

How do I install Professional Brain in Codex?

Run `npx skills add mohitagw15856/pm-claude-skills --skill professional-brain -a codex`. Or copy the skill folder (skills/professional-brain in mohitagw15856/pm-claude-skills) into .agents/skills/professional-brain in your project. Codex loads it when a task matches its description.

Can I use Professional Brain 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 mohitagw15856/pm-claude-skills --skill professional-brain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/professional-brain, .gemini/skills/professional-brain, .github/skills/professional-brain and .opencode/skills/professional-brain in your project.

What does Professional Brain need to run?

Going by SKILL.md and its folder, Professional Brain needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Professional Brain 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 Professional Brain 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Professional Brain use?

Professional Brain 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 Professional Brain use?

About 2.2k tokens (SKILL.md is roughly 8.9k 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 Professional Brain?

Skills that share tags, products or a category with Professional Brain: Wiki Maintainer (openclaw/openclaw, 392k stars), Obsidian Vault Maintainer (openclaw/openclaw, 392k stars), Openclaw PR Maintainer (openclaw/openclaw, 392k stars) and Brain (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Professional Brain?

mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.

Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.