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 agentmods add skills/aegntic/cldcde/ae-proof-agentnpx skills add aegntic/cldcde --skill ae-proof-agentgit clone --depth 1 https://github.com/aegntic/cldcdeWrote 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/aegntic/cldcde/ae-proof-agent)<a href="https://agentmods.dev/skills/aegntic/cldcde/ae-proof-agent"><img src="https://agentmods.dev/badge/skills/aegntic/cldcde/ae-proof-agent.svg" alt="Measured on agentmods" 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 | $0.00085 | $0.00350 |
| Opus 5 | $0.00043 | $0.00175 |
| Sonnet 5 | $0.00017 | $0.00070 |
| Haiku 4.5 | $0.00009 | $0.00035 |
Grade A, and why
ae-proof-agent 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 5d 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
ae-proof-agent
Read references/RESEARCH-GUARDRAILS.md first.
Then use the bundle in this order:
- Read
references/COMPETITIVE-DILIGENCE.md. - Use
references/PRD.mdandreferences/TECHSPEC.mdas the base spec. - Run the prompt chain in
prompts/when generating comparable multi-agent outputs. - Score outputs with
templates/SCORECARD.md. - Assemble the final memo with
templates/FINAL-REPORT-OUTLINE.md.
Rules:
- Separate
Verified,Inference, andUnknown. - Do not invent backend details, customer metrics, or infra choices.
- Use exact dates for recent releases and product changes.
- Prefer primary sources when browsing is required.
- Optimize for decision quality, not volume.
Use the prompt chain like this:
prompts/01-DISCOVERY.mdfor a source-grounded briefprompts/02-PRD.mdfor product requirementsprompts/03-TECHSPEC.mdfor implementation planningprompts/04-REDTEAM.mdfor failure analysisprompts/05-SYNTHESIS.mdfor the final leadership memo
What ships with it
23 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.
- adapters/AGENTS.md 687 B
- adapters/CLAUDE.md 814 B
- adapters/GEMINI.md 570 B
- adapters/OPENCODE.md 452 B
- adapters/PI.md 412 B
- AGENTS.md 590 B
- agents/openai.yaml 380 B
- CLAUDE.md 475 B
- GEMINI.md 365 B
- OPENCODE.md 336 B
- PI.md 222 B
- prompts/00-SYSTEM.md 525 B
- prompts/01-DISCOVERY.md 531 B
- prompts/02-PRD.md 519 B
- prompts/03-TECHSPEC.md 603 B
- prompts/04-REDTEAM.md 539 B
- prompts/05-SYNTHESIS.md 392 B
- references/COMPETITIVE-DILIGENCE.md 4.6 KB
- references/PRD.md 6.9 KB
- references/RESEARCH-GUARDRAILS.md 1.4 KB
- references/TECHSPEC.md 7.4 KB
- templates/FINAL-REPORT-OUTLINE.md 833 B
- templates/SCORECARD.md 783 B
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.
- 5d ago First seen · 33 lines · 85 tokens per session scan A d458480b65d9
ae-proof-agent is a skill published in the GitHub repository aegntic/cldcde (11 stars, last pushed 8d ago), licensed MIT. It adds 85 tokens to every session and 350 once invoked, about $0.0004 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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