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 reatlat/fullstory-claude-plugin --skill changelog-detectivegit clone --depth 1 https://github.com/reatlat/fullstory-claude-pluginWrote 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/reatlat/fullstory-claude-plugin/changelog-detective)<a href="https://agentmods.dev/skills/reatlat/fullstory-claude-plugin/changelog-detective"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/changelog-detective/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/reatlat/fullstory-claude-plugin/changelog-detective"><img src="https://agentmods.dev/badge/skills/reatlat/fullstory-claude-plugin/changelog-detective.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.01493 |
| Opus 5 | $0.00030 | $0.00746 |
| Sonnet 5 | $0.00012 | $0.00299 |
| Haiku 4.5 | $0.00006 | $0.00149 |
Grade A, and why
changelog-detective 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 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.
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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Changelog Detective
Find what actually changed after a deploy — not what the release notes say, but what the session data shows. Catch undocumented changes, side effects, and surprises.
When to Use
- "What actually changed after the deploy?"
- "Something feels different since Tuesday — what changed?"
- "Check for undocumented changes in the last release"
- "Did the deploy introduce any new user behaviors?"
- "What new errors appeared this week that weren't here last week?"
Mental Model
Release notes tell you what was intended to change. Session data tells you what actually changed. These often differ. A "minor CSS fix" might accidentally break form validation. A "performance improvement" might introduce a new race condition. This skill hunts for the gaps between intent and reality.
Workflow
Step 1: Define the comparison window
Two time periods:
- Before: 24-72 hours before the deploy/change date
- After: 24-72 hours after (but not including the deploy window itself — things are chaotic during rollout)
Ask: "I'll compare 48 hours before and after the deploy (excluding the deploy hour). That OK?"
Step 2: Before/After diff — Errors
What errors existed before vs after?
fullstory:build_metric(query="errors by type", output_type="top_n")
fullstory:compute_metric(metric_id, time_range=before)
fullstory:compute_metric(metric_id, time_range=after)
Look for:
- New errors: Error types that appear in After but not Before → these are deploy regressions
- Resolved errors: Error types in Before but not After → these are fixed (celebrate these)
- Changed errors: Same error type, different frequency → possible impact change
Step 3: Before/After diff — Frustrations
fullstory:get_opportunities(time_range=before)
fullstory:get_opportunities(time_range=after)
→ compare the lists
Look for:
- New frustration signals: Rage clicks or dead clicks on elements that weren't problematic before
- Resolved frustrations: Frustrations that disappeared (fix worked!)
- Changed patterns: Same frustration, different page or device distribution
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.
- 12d ago First seen · 134 lines · 60 tokens per session scan A c88b5d93a1aa
changelog-detective is a skill published in the GitHub repository reatlat/fullstory-claude-plugin (62 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 1,493 once invoked, about $0.0003 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 2026-08-30.
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