ai-agent-memory: Skill for Claude Code

.claude/skills/review-sessions/SKILL.md

review-sessions is a skill for Claude Code from ozgurkarahan/ai-agent-memory. It costs 76 tokens per session (1,934 once invoked), scanned A, original, MIT.

A skill for examining coding-agent session records, which are logs of past conversations, commands, and tool use.

In plain words
What is it for?
It is for reviewing GitHub Copilot CLI or Claude Code sessions and finding patterns in efficiency, tool use, errors, and security hygiene.
Why use it?
It helps reveal workflow problems, recurring errors, weak prompts, and security habits from actual sessions.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths; mentions subagents; names the TodoWrite tool.

This is ozgurkarahan/ai-agent-memory's own configuration. It tells Claude Code how to work on ai-agent-memory itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-agent-memory configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ozgurkarahan/ai-agent-memory. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ozgurkarahan/ai-agent-memory/master/.claude/skills/review-sessions/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/ozgurkarahan/ai-agent-memory

Made for: Claude Code.

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 review-sessions

README.md
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Your own site
<a href="https://agentmods.dev/skills/ozgurkarahan/ai-agent-memory/review-sessions"><img src="https://agentmods.dev/badge/skills/ozgurkarahan/ai-agent-memory/review-sessions/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 review-sessions

Your own site · 80×15
<a href="https://agentmods.dev/skills/ozgurkarahan/ai-agent-memory/review-sessions"><img src="https://agentmods.dev/badge/skills/ozgurkarahan/ai-agent-memory/review-sessions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,934 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.01934
Opus 5 $0.00038 $0.00967
Sonnet 5 $0.00015 $0.00387
Haiku 4.5 $0.00008 $0.00193

Measured 11d ago against content hash d09c5f417dd7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

review-sessions 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 11d 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.

.claude/skills/review-sessions/SKILL.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Sessions

When the user says "review sessions", "session review", or invokes /review-sessions, analyse coding-agent session data to identify workflow improvements, prompt-quality patterns, error trends, and security hygiene issues.

Works across both supported agents:

Agent Where sessions live Format
GitHub Copilot CLI ~/.copilot/session-state/{session-id}/events.jsonl (+ plan.md, checkpoints/, command-history-state.json) JSONL event stream — typed events (session.start, session.mode_changed, turn.user, turn.assistant, tool.invoked, …) with timestamp, id, parentId
Claude Code ~/.claude/projects/{project-hash}/{session-id}.jsonl (+ ~/.claude/history.jsonl) JSONL conversation turns — `type: user

Resolve the memory root

  1. If memory/schema.md exists in the current workspace, set WIKI_ROOT to memory/.
  2. Else if schema.md exists, set WIKI_ROOT to the current directory.
  3. Else follow the memory-wiki path in AGENT.md.
  4. If no folder containing both schema.md and index.md can be resolved, report the missing path and stop.

All ops/... paths below are relative to WIKI_ROOT.

Scope modifiers

Interpret these optional modifiers from the user's request:

  • --agent {copilot,claude,all} — source to review; default all
  • --all — ignore the watermark and review every session
  • --project SLUG — match the session cwd or git root
  • --since YYYY-MM-DD — include sessions on or after this date
  • No modifiers — incremental review using ops/review-state.json

Step 1: Discover and normalize sessions directly

Use the agent's native file listing, search, JSON/JSONL reading, and reasoning capabilities. Do not require or create a helper extraction script.

  1. Inventory session files for the selected agent source(s).
  2. For incremental mode, read ops/review-state.json if it exists and exclude namespaced file IDs already present in watermark.reviewed_files. A file ID is copilot:{absolute-path} or claude:{absolute-path}.
  3. Apply project and date filters before reading large files.
  4. Read each JSONL file in manageable chunks. Parse each line independently; count and report malformed lines instead of silently discarding them.
  5. Normalize records into this common in-memory model:
    • agent: copilot or claude
    • session_id, timestamp
    • kind: user_turn, assistant_turn, tool_call, tool_result, error, or mode_change
    • text, tool_name, success, duration_ms when available
  6. Copilot mapping: use event type values such as turn.user, turn.assistant, tool.invoked, tool completion/error events, and session.mode_changed.
  7. Claude mapping: use type: user|assistant records and nested tool_use / tool_result content; infer plan-mode changes only when explicitly represented.
  8. Keep the processed namespaced file IDs for the state update in Step 6.

Read the full file on GitHub · 159 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. 11d ago First seen · 159 lines · 76 tokens per session scan A d09c5f417dd7

Subscribe to this mod's changes

review-sessions is a skill published in the GitHub repository ozgurkarahan/ai-agent-memory (8 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 1,934 once invoked, about $0.0004 per session on Opus 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 2026-08-31.

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