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.
npx skills add cyberelf/agent_skills --skill session-reviewgit clone --depth 1 https://github.com/cyberelf/agent_skillsWrote 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.
[](https://agentmods.dev/skills/cyberelf/agent_skills/session-review)<a href="https://agentmods.dev/skills/cyberelf/agent_skills/session-review"><img src="https://agentmods.dev/badge/skills/cyberelf/agent_skills/session-review/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.
<a href="https://agentmods.dev/skills/cyberelf/agent_skills/session-review"><img src="https://agentmods.dev/badge/skills/cyberelf/agent_skills/session-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00183 | $0.02235 |
| Opus 5.5 | $0.00073 | $0.00894 |
| Sonnet 5.5 | $0.00037 | $0.00447 |
| Haiku 4.5 | $0.00018 | $0.00224 |
Grade A, and why
session-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Review Skill
You are performing a cross-session AI assistant analysis for a software project.
The scripts you need are bundled alongside this SKILL.md in scripts/.
~/.claude/skills/session-review/
├── SKILL.md ← you are here
└── scripts/
├── retro.ts ← orchestrator (run this)
├── get_hist.ts ← raw session collector
└── normalize_hist.ts ← normalizer
Set SKILL_SCRIPTS="$HOME/.claude/skills/session-review/scripts" at the start of any bash
commands you run, so you can refer to scripts as $SKILL_SCRIPTS/retro.ts.
Follow each phase in order. Do not skip phases.
Phase 0 — Determine the project
- If the user invoked this skill with an argument (e.g.
/session-review ~/workspace/crab), use that path asPROJECT_PATH. - Otherwise check the current working directory: if it has
Cargo.toml,package.json,src/, or similar project markers, use$PWD. - If still ambiguous, ask: "Which project path should I analyze?"
PROJECT_NAME is the directory's basename. Storage lives at ~/.retro/<PROJECT_NAME>/.
Phase 1 — Collect and normalize (the pipeline)
SKILL_SCRIPTS="$HOME/.claude/skills/session-review/scripts"
npx tsx "$SKILL_SCRIPTS/retro.ts" "$PROJECT_PATH" run
This runs two steps automatically:
- collect —
get_hist.tscopies raw sessions from Copilot CLI (~/.copilot/session-state), Claude Code (~/.claude/projects/), and VS Code to~/.retro/<PROJECT_NAME>/raw/ - normalize —
normalize_hist.ts --incrementalconverts sessions to unified Markdown in~/.retro/<PROJECT_NAME>/normalized/
On the first run, all sessions are collected. On subsequent runs, only sessions newer
than lastCollectedAt in the manifest are added.
If the user wants a full re-analysis from scratch, add --full:
npx tsx "$SKILL_SCRIPTS/retro.ts" "$PROJECT_PATH" run --full
If the pipeline exits non-zero, read its stderr to diagnose before continuing.
Check progress anytime:
npx tsx "$SKILL_SCRIPTS/retro.ts" "$PROJECT_PATH" status
What ships with it
3 files 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.
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.
- 2mo ago First seen · 290 lines · 183 tokens per session scan A f80b68c85fd3
session-review is a skill published in the GitHub repository cyberelf/agent_skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 183 tokens to every session and 2,235 once invoked, about $0.0007 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 2026-08-31.
session-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| session-reviewcyberelf/agent_skills | Skill | 2 | 2mo ago | MIT | A | 183 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |