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 britt/agent-skills --skill context-aware-questionsgit clone --depth 1 https://github.com/britt/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/skills/britt/agent-skills/context-aware-questions)<a href="https://agentmods.dev/skills/britt/agent-skills/context-aware-questions"><img src="https://agentmods.dev/badge/skills/britt/agent-skills/context-aware-questions/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/britt/agent-skills/context-aware-questions"><img src="https://agentmods.dev/badge/skills/britt/agent-skills/context-aware-questions.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 | $0.00040 | $0.00998 |
| Opus 5 | $0.00020 | $0.00499 |
| Sonnet 5 | $0.00008 | $0.00200 |
| Haiku 4.5 | $0.00004 | $0.00100 |
Grade A, and why
context-aware-questions 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 9d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context-Aware Question Generator Skill
Analyze project context to surface information gaps and generate prioritized, actionable questions.
When to Use
Activate when:
- User asks "what am I missing?" or "what questions should I be asking?"
- Reviewing issues before starting work
- Analyzing documentation completeness
- Preparing a draft (issue, PR, document) for submission
- During project planning or kickoff
Fetching Issues
Where issues are needed, fetch them with the gh CLI (must be installed and authenticated):
gh issue list --state open --json number,title,body,labels,assignees
gh issue view <n> --comments
Analysis Modes
1. Project-Wide Review
When asked "what am I missing?" or "what questions should I be asking?":
- Fetch all open issues (see Fetching Issues)
- Analyze project structure
- Check README and documentation
- Analyze all gathered data for information gaps
- Generate prioritized questions
2. Issue Review
When asked to review a specific issue:
- Fetch the issue and all comments (see Fetching Issues)
- Analyze for missing requirements, unclear specs, and gaps
- Generate targeted questions for that issue
3. Draft Review
When reviewing a draft (issue, PR, note) before submission:
- Analyze the provided text for completeness
- Check against standard templates and best practices
- Suggest specific improvements
4. Documentation Gap Analysis
When asked about documentation completeness:
- Read README.md and files in docs/
- Analyze what the project contains
- Identify missing documentation by comparing project content to docs
Gap Detection Heuristics
Issue Analysis
- Missing acceptance criteria: No checkboxes, no "done when" statement
- Vague descriptions: Less than 100 characters, contains "unclear", "might", "maybe"
- Missing labels or assignees: Issue has no labels or no assignee
- Stale issues: Open more than 30 days with no activity
- Bug reports without reproduction steps: No "steps to reproduce" section
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.
- 9d ago First seen · 137 lines · 40 tokens per session scan A 9654e05b1bad
context-aware-questions is a skill published in the GitHub repository britt/agent-skills (5 stars, last pushed 6d ago), licensed MIT. It adds 40 tokens to every session and 998 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.
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