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 antropos17/Aegis --skill prompt-craftgit clone --depth 1 https://github.com/antropos17/AegisWrote 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/antropos17/aegis/prompt-craft)<a href="https://agentmods.dev/skills/antropos17/aegis/prompt-craft"><img src="https://agentmods.dev/badge/skills/antropos17/aegis/prompt-craft/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/antropos17/aegis/prompt-craft"><img src="https://agentmods.dev/badge/skills/antropos17/aegis/prompt-craft.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 | $0.00364 |
| Opus 5.5 | $0.00012 | $0.00146 |
| Sonnet 5.5 | $0.00006 | $0.00073 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
prompt-craft 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 today.
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
Write an AEGIS task prompt
State the requested result, relevant observed files and behavior, and validation needed to assess completion. Make the prompt self-contained, while leaving routine implementation decisions flexible. A prompt-writing request asks for a prompt; do not execute it, create a separate task or invoke another agent unless requested.
Read AGENTS.md and verify the actual checkout before naming paths. Vite determines the renderer root; frontend/observatory/ is not present in every checkout. Existing implementation is evidence to inspect, not a reason to claim a reported bug is already fixed without verifying the behavior.
For UI integration, use the applicable approved design and design-system guidance. For a new visual exploration, preserve the user's freedom to explore alternatives and distinguish concept delivery from integration.
For monitoring/backend changes, include only relevant identity, outage, platform and measurement invariants. Consult the applicable failure history in memory-bank/ai-mistakes.md when needed.
Describe checks for the behavior being changed, using package.json and docs/development/workflow.md. Use project-aware typecheck commands rather than bare tsc against the solution. Rendered checks apply to UI implementation; prototype-only work needs artifact review. Do not require an unavailable MCP, external AI CLI or subagent.
Carry forward the session's authorization for reversible changes and the Git cycle where relevant. For tracked source work use an appropriate codex/ feature branch/worktree without disturbing dirty parallel work. Do not add routine plan/push approval questions, arbitrary limits on steps/files, a mandatory prompt formula, or automatic recurring monitoring. Preserve explicit boundaries for releases and protected files from AGENTS.md.
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.
- today First seen · 19 lines · 31 tokens per session scan A cf8d5c93eb87
prompt-craft is a skill published in the GitHub repository antropos17/Aegis (157 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 364 once invoked, about $0.0001 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 2026-10-17.
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