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 techhorizonlabs/thl-open --skill agent-readiness-scangit clone --depth 1 https://github.com/techhorizonlabs/thl-openWrote 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/techhorizonlabs/thl-open/agent-readiness-scan)<a href="https://agentmods.dev/skills/techhorizonlabs/thl-open/agent-readiness-scan"><img src="https://agentmods.dev/badge/skills/techhorizonlabs/thl-open/agent-readiness-scan/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/techhorizonlabs/thl-open/agent-readiness-scan"><img src="https://agentmods.dev/badge/skills/techhorizonlabs/thl-open/agent-readiness-scan.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 | $0.00079 | $0.01128 |
| Opus 5 | $0.00039 | $0.00564 |
| Sonnet 5 | $0.00016 | $0.00226 |
| Haiku 4.5 | $0.00008 | $0.00113 |
Grade A, and why
agent-readiness-scan scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
3. **Scored vs supplementary.** llms.txt, llms-full.txt, security.txt are NOT scored by Cloudflare but Theo audits track them — they go in `Supplementary (not scored)` rows from curl probes, never mixed into scored categ How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent-Readiness Scan (isitagentready.com)
Produce the official Cloudflare agent-readiness result for a domain as audit-grade artifacts: fixed-schema CSV + raw evidence + the 0-100 score.
Critical facts (learned the hard way)
- Two sources, both required:
POST https://isitagentready.com/api/scanbody{"url":"https://<domain>"}→ full JSON (level, levelName, per-check status + embedded request/response evidence, nextLevel remediation prompts + skillUrls). No numeric score in the JSON.- The 0-100 score renders only in the web UI. Playwright-navigate to
https://isitagentready.com/<host>and read the score dial: an<svg>carryingaria-label="Overall score: N out of 100". Neverwait_forthat text — it's an attribute, not visible text (text-waits time out). Take a page snapshot or evaluatedocument.querySelector('[aria-label*="Overall score"]'). A fresh "Last scanned" timestamp = results are rendered (the step-1 API POST itself refreshes the scan, so no Scan click is normally needed). Without the 0-100 you cannot track deltas (e.g. a site improving 21→43 after fixes).
- Don't freeze the checklist. The scanner evolves (new checks appear). Emit whatever
.checksreturns, mapped through the fixed CSV schema — never hand-author check rows. - Scored vs supplementary. llms.txt, llms-full.txt, security.txt are NOT scored by Cloudflare but Theo audits track them — they go in
Supplementary (not scored)rows from curl probes, never mixed into scored categories. - Commerce is informational unless
isCommerceis true — oneNOT CHECKEDrow, "does not affect score".
Workflow
scripts/run_scan.sh https://<domain> <outdir>/raw-data
Then get the official score via Playwright (see Critical fact 1 for the exact method). Save the page snapshot to raw-data/isitagentready_<client-slug>_snapshot.txt (client slug, e.g. acme — matches your audit config slug). Then:
python3 scripts/scan_to_csv.py \
<outdir>/raw-data/iar_scan.json --score <N> --out <outdir>/csv-base-data/agent_readiness_checks.csv
(csv-base-data/ is the Theo full-pack convention; scoped snapshots have used plain csv/ — either is fine, pass --out explicitly.)
What ships with it
2 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.
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 · 55 lines · 79 tokens per session scan A 2bf25b6b8490
agent-readiness-scan is a skill published in the GitHub repository techhorizonlabs/thl-open (15 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 1,128 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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