replay-learnings

replay-learnings is a skill for Claude Code, Codex from strikersam/autonomous-ai-agency. It costs 34 tokens per session (713 once invoked), scanned B, original, MIT.

A preparation step that reads a project's stored lessons from earlier work and selects the ones relevant to the current task. It also checks recent task checkpoints.

In plain words
What is it for?
Use it at the start of a coding session, before revisiting a module, after resuming paused work, or when asking what the project has learned about a topic.
Why use it?
It helps an agent remember project-specific rules and avoid repeating known mistakes before changing code.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; installed under .agents/ (shared by several agents).

Good fit Use it at the start of a coding session, before revisiting a module, after resuming paused work, or when asking what the project has learned about a topic.

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Install with agentmods
npx agentmods add skills/strikersam/autonomous-ai-agency/replay-learnings
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 strikersam/autonomous-ai-agency --skill replay-learnings
Clone the repo
git clone --depth 1 https://github.com/strikersam/autonomous-ai-agency

Made for: Claude Code, Codex.

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.

agentmods badge for replay-learnings

README.md
[![agentmods](https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/replay-learnings/github.svg)](https://agentmods.dev/skills/strikersam/autonomous-ai-agency/replay-learnings)
Your own site
<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/replay-learnings"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/replay-learnings/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.

agentmods 80×15 button for replay-learnings

Your own site · 80×15
<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/replay-learnings"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/replay-learnings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 713 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00034 $0.00713
Opus 5 $0.00017 $0.00357
Sonnet 5 $0.00007 $0.00143
Haiku 4.5 $0.00003 $0.00071

Measured 12d ago against content hash 03025d4c8a3f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade B, and why

replay-learnings scanned grade B with 1 finding 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 12d 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

cat .claude/state/learnings.md
.agents/skills/replay-learnings/SKILL.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: replay-learnings

When to Use

Run this skill:

  • At the start of a new session before touching any code
  • Before working on a module you've touched before
  • After cooldown-resume loads the checkpoint (learnings provide extra context)
  • When the user asks "what did we learn about X?"

Instructions

Step 1 — Read the learnings file

cat .claude/state/learnings.md

If the file doesn't exist, skip to Step 3 (no learnings yet).

Step 2 — Filter relevant learnings

From all entries, extract those relevant to the current task. Match by:

  • Module name — does the learning mention a file you're about to touch?
  • Operation type — does the learning apply to commits, auth, routing, tests?
  • Keyword overlap — does the learning's situation match the current context?

Present the relevant learnings as a short list:

Relevant learnings for this task:
- [2026-03-15] Never use git add -A — stage specific files only.
- [2026-03-22] Always read router/CLAUDE.md before touching model_router.py.
- [2026-04-01] risky-module-review is required for admin_auth.py even for 1-line changes.

Step 3 — Check recent checkpoint history

tail -20 .claude/state/checkpoint.jsonl 2>/dev/null || echo "No checkpoint history."

Look for patterns:

  • Steps that were retried (same step_id appearing twice)
  • Steps that failed
  • Any "partial" status entries

Step 4 — Surface blockers from previous session

cat .claude/state/NEXT_ACTION.md 2>/dev/null || echo "No next action file."

Check for documented blockers that are still unresolved.

Step 5 — Apply relevant rules

Before starting work, briefly confirm which rules apply:

Applying rules from learnings:
✓ Will stage specific files (not git add -A)
✓ Will read router/CLAUDE.md before touching routing code
✓ Will invoke risky-module-review for auth module

Learnings File Doesn't Exist?

This is expected on a fresh clone. The file is created by learn-rule and wrap-up. Start working, and the learnings will accumulate over time.

Read the full file on GitHub · 103 lines

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.

  1. 12d ago First seen · 103 lines · 34 tokens per session scan B 03025d4c8a3f

Subscribe to this mod's changes

replay-learnings is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 713 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.