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/iamsecure1920/cordon-ai/cordon-reportnpx skills add iamsecure1920/Cordon-AI --skill cordon-reportgit clone --depth 1 https://github.com/iamsecure1920/Cordon-AIWrote 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/iamsecure1920/cordon-ai/cordon-report)<a href="https://agentmods.dev/skills/iamsecure1920/cordon-ai/cordon-report"><img src="https://agentmods.dev/badge/skills/iamsecure1920/cordon-ai/cordon-report.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 5.1 | $0.00055 | $0.00680 |
| Opus 5 | $0.00028 | $0.00340 |
| Sonnet 5 | $0.00011 | $0.00136 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
cordon-report 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.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cordon reporting
findings_list(status="confirmed")
findings_list(status="needs_manual_review")
report_generate()
Writes Report.md, Report.csv, findings.json, and taskgraph.mmd into the
engagement's reports/ directory, alongside evidence/ and audit.jsonl.
The structure, and why
Confirmed findings — each with a reproduction a triager can run without asking you a question. If a finding needs a follow-up email to reproduce, it is not finished.
Needs manual review — a separate section, explicitly labelled unproven. Never blend these into the confirmed section to make the report look fuller. A triager who finds one unproven item among your confirmed ones will re-check all of them, and you will have spent credibility that took months to build.
Scope, methodology, tool inventory, cost — how a reader checks your work. The task graph shows why each step happened; the audit log records every request, including the refusals.
Before you hand it over
Read Report.md yourself and check:
- Every confirmed finding reproduces from the document alone.
- Nothing unproven leaked into the confirmed section.
- Severity matches the evidence, not the vulnerability class's potential. An
exposed
.envwith live AWS keys is critical. An exposed.envcontaining onlyAPP_NAMEis not, however much the filename suggests otherwise. - Impact is stated in the target's terms — what an attacker gets — not in terms of the vulnerability's name.
impact_limit_noteis present on every PoC, so the program can see exactly how far you went.
Partial reports
If a budget ceiling fired, the report is labelled PARTIAL on its first page and states that coverage is incomplete. Leave that label in place. "We ran out of budget at 60% coverage" is honest and useful; silently shipping a partial report as complete tells the program their surface is clean when you never looked.
Severity honesty
The most common way to lose a program's trust is inflating severity. Some specifics:
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 · 73 lines · 55 tokens per session scan A c43918e24c01
cordon-report is a skill published in the GitHub repository iamsecure1920/Cordon-AI (0 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 680 once invoked, about $0.0003 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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