A session-learning tool that records recurring patterns, decisions, and unusually costly work. It promotes patterns that appear at least three times into a shared decisions file.

Use it to extract lessons from a work session and maintain files of repeatable practices and project decisions.

It reduces the chance that useful lessons or past decisions are forgotten between sessions. It also highlights repeated sources of cost.

pm-learn — Skill for Claude Code and Codex by VandanaAjayDubey111

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add VandanaAjayDubey111/great-pm --skill pm-learn

Clone the repo

git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pm

Made for: Claude Code, Codex.

Or install great-pm, the plugin that ships this one along with the rest of its 114 skills, 34 commands, 48 agents, 5 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/pm-learn/github.svg)](https://agentmods.dev/skills/vandanaajaydubey111/great-pm/pm-learn)

Your own site

<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/pm-learn"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/pm-learn/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/vandanaajaydubey111/great-pm/pm-learn"><img src="https://agentmods.dev/badge/skills/vandanaajaydubey111/great-pm/pm-learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,087 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00056	$0.01087
Opus 5.5	$0.00022	$0.00435
Sonnet 5.5	$0.00011	$0.00217
Haiku 4.5	$0.00006	$0.00109

Measured 29d ago against content hash 0a7b6ce14faf, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pm-learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 29d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/great-pm/skills/pm-learn/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codex host binding

Treat references to Claude slash workflows as the equivalently named Codex skill.
Before delegating to any specialist, read the great-pm-runtime skill and the selected packaged role file.
Treat "invoke", "assign", "delegate", "spawn", and source Agent-tool instructions as a required Codex spawn_agent call with that role and a bounded assignment.
For the spawn tool's task_name or agent_name identifier, replace canonical role-name hyphens with underscores (query-refiner-pm → query_refiner_pm). Keep canonical names unchanged in prompts, filenames, verdict logs, and user-facing output; this is an internal identifier mapping, not a role rename.
Store every returned agent identifier. Never call a wait tool until a spawn has returned an identifier, and wait only on identifiers returned by successful spawns.
If spawn_agent is unavailable or a spawn fails, report BLOCKED; do not impersonate the specialist or wait on an empty agent set.
Resolve bundled paths from the installed GreatPM plugin root.
Ignore Claude-only model aliases, colors, turn limits, and tool allowlists.
Preserve GreatPM human gates, governance, state, and reporting contracts.

You are the great-pm $pm-learn command. Capture session learnings without requiring a full $pm-save.

Parse arguments

--dry-run → continuous-learner produces the lessons block but does NOT write it to disk. Print preview only.
(no flag) → write to .great-pm/lessons.md and promote ≥3-occurrence patterns to ~/.great-pm/decisions.md.

Pre-flight

echo "cwd=$(pwd)"
mkdir -p .great-pm
ls .great-pm/lessons.md 2>/dev/null && echo "LESSONS_OK" || echo "FIRST_RUN"
ls .great-pm/.learn-pending 2>/dev/null && echo "PENDING_MARKER" || echo "NO_MARKER"

If PENDING_MARKER exists → this is the recommended path (SessionEnd hook flagged something worth capturing).

Operating procedure

Step 0 — refine the user's query (transparent Mode B). Invoke query-refiner-pm with $ARGUMENTS. The refiner returns:
```
You typed:  <original>

Refined to: <refined brief>

What changed: <one line>

Proceeding with refined. Reply "use original" to override.
```
Use the refined version as the brief for subsequent steps UNLESS the user replies "use original". Log the refinement to .great-pm/refinements/$(date +%Y-%m-%d).log. This wiring is universal across great-pm commands per the gate-policy: explicit discipline — you make the user's leverage visible while preserving their ability to override.

Read the full file on GitHub · 96 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

agents/openai.yaml 221 B

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

29d ago First seen · 96 lines · 56 tokens per session scan A 0a7b6ce14faf

Subscribe to this mod's changes

pm-learn is a skill published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 1,087 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.

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