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 ai-driven-dev/framework --skill 03-shadow-areasgit clone --depth 1 https://github.com/ai-driven-dev/frameworkWrote 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/ai-driven-dev/framework/03-shadow-areas)<a href="https://agentmods.dev/skills/ai-driven-dev/framework/03-shadow-areas"><img src="https://agentmods.dev/badge/skills/ai-driven-dev/framework/03-shadow-areas/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/ai-driven-dev/framework/03-shadow-areas"><img src="https://agentmods.dev/badge/skills/ai-driven-dev/framework/03-shadow-areas.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 | $0.00054 | $0.00523 |
| Opus 5.5 | $0.00022 | $0.00209 |
| Sonnet 5.5 | $0.00011 | $0.00105 |
| Haiku 4.5 | $0.00005 | $0.00052 |
Grade A, and why
03-shadow-areas 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 1mo 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shadow Areas
Analytically scans a written artifact for gaps the author has not addressed. Unlike iterative Q&A clarification, this skill reads the existing material and emits a structured report: each gap carries a category from a locked 7-category taxonomy, a 3-tier severity, and a direct-question probe the author can act on immediately.
Actions
| # | Action | Role | Input |
|---|---|---|---|
| 01 | detect |
Parse input, extract gaps, classify category and severity, emit probes | file path or inline text |
| 02 | render-report |
Render markdown grouped by category and sorted by severity, write report | gap list from detect |
| 03 | diff |
Load prior report, classify gaps as closed / still-open / newly-introduced | gap list from detect + prior report path |
Dispatch by context: with no prior report run detect then render-report; with one, run detect then diff.
Before running an action, read its file in actions/, not only the table or assets.
Transversal rules
- Never modify the source artifact.
- Every gap carries all three: a category, a severity, and a probe question.
- Every probe is a direct question ending with
?. - Categories and severities come from the locked sets in
references/locked-sets.json. - When zero blockers and zero majors remain, stamp the report
status: clean. - On re-runs, gaps are matched by category and snippet, never by question wording, so rephrasing a question never creates a spurious "newly introduced" gap.
References
references/categories.md: locked 7-category taxonomy with definition and example per category.references/severity-rubric.md: blocker / major / minor decision rules and examples.references/probe-style.md: direct-question form rules.references/locked-sets.json: machine-readable sets reused by the validator.
What ships with it
8 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.
- 1mo ago First seen · 41 lines · 54 tokens per session scan A d641ad61c524
03-shadow-areas is a skill published in the GitHub repository ai-driven-dev/framework (518 stars, last pushed today), licensed MIT. It adds 54 tokens to every session and 523 once invoked, about $0.0002 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 2026-09-03.
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