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 HenriqueCotta/ownership-driven-ai-customization-architecture --skill impact-reviewgit clone --depth 1 https://github.com/HenriqueCotta/ownership-driven-ai-customization-architectureWrote 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/henriquecotta/ownership-driven-ai-customization-architecture/impact-review)<a href="https://agentmods.dev/skills/henriquecotta/ownership-driven-ai-customization-architecture/impact-review"><img src="https://agentmods.dev/badge/skills/henriquecotta/ownership-driven-ai-customization-architecture/impact-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/henriquecotta/ownership-driven-ai-customization-architecture/impact-review"><img src="https://agentmods.dev/badge/skills/henriquecotta/ownership-driven-ai-customization-architecture/impact-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 | $0.00031 | $0.00272 |
| Opus 5 | $0.00015 | $0.00136 |
| Sonnet 5 | $0.00006 | $0.00054 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
impact-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 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.
What it actually says
Impact Review
Use this skill when:
- a change may affect more than its origin path
- the repository's follow-through policy still needs a concrete decision in the current task
- you need to decide between no action, immediate reconciliation, or explicit follow-up
Workflow
- Confirm the originating change and the requested scope.
- Find the relevant ownership nodes, overlays, and
Follow-Through Triggers. - Build a short list of downstream surfaces that could realistically matter.
- Inspect only the surfaces whose state could still change the decision.
- Decide which surfaces need no action, an update now, or explicit carry-forward.
- Use scripts, CI, or runbooks for exact repeatable checks.
- Finish by stating what was updated, what was intentionally deferred, and where that follow-through now lives if it matters.
Guardrails
- Do not enumerate the whole repository by default.
- Do not treat every trigger as a command to widen scope aggressively.
- Do not leave meaningful follow-through implicit if the current pass is not closing it.
- Do not create a new skill per trigger shape when this workflow is still sufficient.
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 · 30 lines · 31 tokens per session scan A 6fbce8cdebc7
impact-review is a skill published in the GitHub repository HenriqueCotta/ownership-driven-ai-customization-architecture (5 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 272 once invoked, about $0.0002 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.
Other skills, from other repositories
plan-task
Create a detailed implementation plan before coding. Use when starting a new feature, multi-step refactor, or complex task. Invoked by saying "plan", "create a plan", or "plan this task".
commit-all
Batch-commit all uncommitted changes grouped by relevance. Use when multiple accumulated changes need committing. Invoked by saying "commit all" or "commit everything".
commit
Stage, commit, and push code changes with branch safety and explicit staging. Use when ready to commit work. Invoked by saying "commit", "push", or "commit and push".
document-task
Document completed work — update task log, sync documentation, log observations. Use after finishing a task or batch of changes.
report
Generate a structured report on completed work, a feature area, or a topic. Saved to the reports directory. Invoked by saying "report", "generate report", or "summarize work".
merge-master
Merge dev branch into master/main and push. Use when dev changes are ready for production branch. Invoked by saying "merge to master" or "merge to main".