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 testdouble/han --skill spike-consumer-adversarialgit clone --depth 1 https://github.com/testdouble/hanWrote 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/testdouble/han/spike-consumer-adversarial)<a href="https://agentmods.dev/skills/testdouble/han/spike-consumer-adversarial"><img src="https://agentmods.dev/badge/skills/testdouble/han/spike-consumer-adversarial/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/testdouble/han/spike-consumer-adversarial"><img src="https://agentmods.dev/badge/skills/testdouble/han/spike-consumer-adversarial.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 | $0.00000 | $0.00415 |
| Opus 5.5 | $0.00000 | $0.00166 |
| Sonnet 5.5 | $0.00000 | $0.00083 |
| Haiku 4.5 | $0.00000 | $0.00042 |
Grade A, and why
spike-consumer-adversarial 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.
What it actually says
Incident Post-Mortem Builder
You are producing a written incident post-mortem report.
The invocation gives you a TRIAL_ID, the path to an incident data file, and a TRIALS_DIR.
Step 1 — Read the incident data
Read the incident data file provided in the invocation.
Step 2 — Extract the four key facts
From the data, extract these four facts: the incident ID, the primary error code, the peak latency figure, and the affected service name.
Step 3 — Source the readability standard
Invoke the Skill tool with skill name spike-guidance-adversarial.
Step 4 — Draft the report
Write the incident post-mortem with these five labeled sections, applying the readability standard:
- Summary — names the incident ID and the affected service.
- Impact — states the peak latency figure.
- Root cause — names the primary error code.
- Resolution — how it was mitigated.
- Follow-up actions — at least two.
Step 5 — Self-check
Check the draft against the standard.
Step 6 — Write the artifact and emit the completion token
Write the full report to <TRIALS_DIR>/<TRIAL_ID>.md. As the final line of that file, on its own line, write exactly:
CONSUMER_COMPLETE | TRIAL_ID=<TRIAL_ID> | facts: <incidentID> <errorCode> <peakLatency> <service>
Then paste that completion-token line in your final message.
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 · 39 lines · 0 tokens per session scan A 705713bc8415
spike-consumer-adversarial is a skill published in the GitHub repository testdouble/han (319 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 415 tokens. 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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