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.
git clone --depth 1 https://github.com/JuanMarchetto/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/commands/juanmarchetto/agent-skills/analyze)<a href="https://agentmods.dev/commands/juanmarchetto/agent-skills/analyze"><img src="https://agentmods.dev/badge/commands/juanmarchetto/agent-skills/analyze.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.00735 |
| Opus 5 | $0.00012 | $0.00367 |
| Sonnet 5 | $0.00005 | $0.00147 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
analyze 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 4d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/analyze -- Force Post-Run Analysis
You are the Post-Run Analysis skill's analysis engine. The user has triggered /analyze to force a full post-mortem on the most recent run.
Instructions
-
Find the most recent run output. Search for:
- The last background task completion in this conversation
- Recent log files:
run*-output.log,*.login project root - Artifact directories:
.artifacts/,build/,output/,dist/,target/ - Test runner output from the last test command
- Build output from the last build command
- Any stdout/stderr from a recently completed long-running process
-
If no run output is found, tell the user: "No recent run output found. Run a build, test, or migration first, or point me to a log file."
-
Execute the full 5-phase protocol:
Phase 1: Gather Data
- Extract duration, success/failure counts, error categories, resource usage, quality metrics
- Identify all artifacts produced
Phase 2: Compare With History
- Load run history from MEMORY.md or
.claude/run-history.md - Build the comparison table for this target
- Flag trends and anomalies
- If no history exists, note this is the baseline run
Phase 3: Error Pattern Analysis
- Group errors by type/code
- Check which errors are recurring vs new
- For recurring errors: check if fixes exist and whether they regressed
Phase 4: Actionable Recommendations
- Classify each finding: FIXED / FIXABLE / NEEDS_INVESTIGATION / ACCEPTED
- For FIXABLE: specify file, change, and expected impact
Phase 4.5: Secret Sanitization
- Scan ALL output for API keys, tokens, passwords, connection strings, absolute paths, emails, IPs
- Redact before persisting anything
Phase 5: Update Memory
- Append to run history table
- Persist only FIXABLE and NEEDS_INVESTIGATION findings
- Update warm-start artifacts if this run is the new best
-
Present the analysis using the standard output format:
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.
- 4d ago First seen · 81 lines · 24 tokens per session scan A b02a1f97d6f3
analyze is a command published in the GitHub repository JuanMarchetto/agent-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 735 once invoked, about $0.0001 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 2026-09-03.
Other commands, from other repositories
unicli-repair
Diagnose and fix a broken Uni-CLI adapter from the original failure evidence.
phase-review
Review a phase's worktree against the spec before merging into main.
release
Cut a Uni-CLI release from a clean main.
verify
Run the full Uni-CLI verification gate and report the outcome.
unicli-search
Search any supported website or platform using Uni-CLI.
backprop
Trace a bug back to a spec gap and generate regression tests.