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 irfad7/claude-power-skills --skill session-reviewgit clone --depth 1 https://github.com/irfad7/claude-power-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/irfad7/claude-power-skills/session-review)<a href="https://agentmods.dev/skills/irfad7/claude-power-skills/session-review"><img src="https://agentmods.dev/badge/skills/irfad7/claude-power-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/irfad7/claude-power-skills/session-review"><img src="https://agentmods.dev/badge/skills/irfad7/claude-power-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 | $0.00093 | $0.01371 |
| Opus 5 | $0.00046 | $0.00685 |
| Sonnet 5 | $0.00019 | $0.00274 |
| Haiku 4.5 | $0.00009 | $0.00137 |
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 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.
This is a copy
97% identical to session-review — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Review — Learning Extraction & Transfer
You are a session reviewer. You analyze what happened during a work session and extract everything worth remembering — decisions, patterns, surprises, wins, and lessons.
When To Run
- At the end of every meaningful work session
- When the user asks for a summary or debrief
- During weekly reviews
- Before context compression (preserve key learnings first)
- When switching to a different project/context
The Review Process
Phase 1: Session Replay
Scan the full conversation and categorize everything that happened:
Work Completed:
- Files created or modified (list with purpose)
- Features built or bugs fixed
- Commands/queries run
- Deployments made
Decisions Made:
- Architecture choices and their rationale
- Technology selections
- Trade-offs accepted
- Alternatives considered and rejected (and why)
Problems Encountered:
- Errors hit and how they were resolved
- Approaches that failed (and why)
- Workarounds applied
- Remaining blockers
Discoveries:
- Things learned about the codebase
- Surprising behavior uncovered
- Undocumented features or quirks found
- Dependencies or constraints discovered
People & Communication:
- People mentioned or involved
- Commitments made
- Questions raised that need answers from others
- Feedback received
Phase 2: Pattern Extraction
Look for patterns that should be captured for future sessions:
Reusable Patterns:
- Code patterns that worked well (potential for abstraction)
- Debugging techniques that were effective
- Workflow shortcuts discovered
- Tool configurations that helped
Anti-Patterns:
- Approaches that wasted time
- Assumptions that proved wrong
- Recurring friction points
- Things that should have been done differently
Process Observations:
- Did the plan match the execution?
- Where did scope creep happen?
- What took longer than expected? Shorter?
- Were the right tools used for the job?
Phase 3: Knowledge Delta
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.
- 11d ago First seen · 196 lines · 93 tokens per session scan A d0ba840fa116
session-review is a skill published in the GitHub repository irfad7/claude-power-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 93 tokens to every session and 1,371 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to session-review, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
interactive-planning
File-based planning with interactive gates and native task tracking. Use when user says /plan, needs to break a complex feature into phases, or wants structured implementation planning with user approval at key decision points. Supports task mode (single plan file) and spec mode (multi-file architecture).
memstack-automation-n8n-workflow-builder
Use this skill when the user says 'n8n workflow', 'build a workflow', 'automation workflow', 'connect services', or needs visual workflow design with node mapping, data transformations, and error handling for n8n. Do NOT use for standalone webhook endpoints or cron jobs.
rtk-optimizer
Wrap high-verbosity shell commands with RTK to reduce token consumption. Use when running git log, git diff, cargo test, pytest, or other verbose CLI output that wastes context window tokens.
session-save
Save the current session state (decisions, modified files, current status, and next steps) to a handoff file for later resume.
memstack-automation-cron-scheduler
Use this skill when the user says 'cron job', 'scheduled task', 'run every', 'cron expression', 'recurring job', or needs production-grade scheduled jobs with overlap prevention, monitoring, and structured logging. Do NOT use for n8n workflows or event-driven webhooks.
handoff-update
Update an existing handoff document with current session progress. Applies section-specific merge rules: append-only for Work Done (never deletes history), replace for Status and Next Steps, merge for Files and Discoveries. Falls back to creating a new handoff if no source file is found.