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 Hmbown/Wizards-of-the-Ghosts --skill identifygit clone --depth 1 https://github.com/Hmbown/Wizards-of-the-GhostsWrote 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/hmbown/wizards-of-the-ghosts/identify)<a href="https://agentmods.dev/skills/hmbown/wizards-of-the-ghosts/identify"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/identify/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/hmbown/wizards-of-the-ghosts/identify"><img src="https://agentmods.dev/badge/skills/hmbown/wizards-of-the-ghosts/identify.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 | $0.00050 | $0.00862 |
| Opus 5 | $0.00025 | $0.00431 |
| Sonnet 5 | $0.00010 | $0.00172 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade A, and why
identify 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 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.
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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identify
Explain what a mysterious file, service, workflow, or artifact actually does.
What This Skill Does
Identify is static analysis for operational understanding. It answers "What is this?" by inspecting structure, naming, dependencies, and runtime touchpoints. It does NOT search for artifacts, debug failures, monitor systems, verify claims, or modify code. In this grimoire, Identify is treated as a metaphorical spell with a shipping-now delivery profile. Canonical reference input: Identify (spell).
When To Use
- Use this spell when a user presents a specific artifact (file, script, config, service, binary, module, chart, extension, etc.) and asks any variation of:
- "What does this do?"
- "Explain this [artifact]"
- "What is this for?"
- "What does it touch/depend on?"
- "What can we prove from inspection?"
- "What's the safest next validation step?"
- Key signal: The artifact is already in hand. The question is about understanding, not finding, fixing, watching, or changing it.
Prerequisites
- No extra runtime dependencies beyond Hermes Agent and the normal toolset for this session.
Procedure
- Restate the target, the success condition, and any no-touch boundaries before taking action.
- Restate boundaries: Name the target, the success condition, and any no-touch constraints before acting.
- Inspect directly: Read the artifact's contents. Do not speculate before looking.
- Infer from evidence: Determine purpose from structure, dependencies, naming conventions, and runtime touchpoints (ports, volumes, secrets, APIs, services).
- Separate certainty levels: Classify findings as:
- Confirmed (directly visible in the artifact)
- Likely (strong inference from patterns/contexts)
- Unknown (cannot be proven without runtime testing or external data)
- Return structured output: Provide:
- Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.
Deliverables
- A plain-English explanation of the artifact.
- Inputs, outputs, dependencies, and side effects when known.
- A confidence-rated list of unknowns.
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 · 82 lines · 50 tokens per session scan A de5065be4b99
identify is a skill published in the GitHub repository Hmbown/Wizards-of-the-Ghosts (107 stars, last pushed 5mo ago), licensed CC0-1.0. It adds 50 tokens to every session and 862 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 2026-09-03.
Other skills, from other repositories
linter-agent
Use when detecting and fixing code style violations, enforcing project conventions, ensuring consistent formatting.
perf-agent
Use when measure before optimizing, target actual bottlenecks proven by profiling, verify with benchmarks.
manage-skills
A maintenance workflow for checking whether project verification skills still cover the code and rules that changed during a session.
systematic-debugging
Structured debugging methodology — use before proposing fixes for any error or failure. Covers: code bugs, build errors, deploy failures, config conflicts, dependency issues, infra problems. Also use when previous fix attempts failed or root cause is unclear.
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
reproduce
Reproduce a cloudflare/agents GitHub issue by scaffolding a minimal Agents/Worker project and deploying it to a temporary Cloudflare account, then report findings back on the issue.