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 hssh8917/cc-skills --skill training-reportgit clone --depth 1 https://github.com/hssh8917/cc-skillsWrote 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/hssh8917/cc-skills/training-report)<a href="https://agentmods.dev/skills/hssh8917/cc-skills/training-report"><img src="https://agentmods.dev/badge/skills/hssh8917/cc-skills/training-report/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/hssh8917/cc-skills/training-report"><img src="https://agentmods.dev/badge/skills/hssh8917/cc-skills/training-report.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 | $0.00179 | $0.02392 |
| Opus 5.5 | $0.00072 | $0.00957 |
| Sonnet 5.5 | $0.00036 | $0.00478 |
| Haiku 4.5 | $0.00018 | $0.00239 |
Grade A, and why
training-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 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.
This is a copy
98% identical to training-report — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Training Report
Iterate the full report in Markdown first. Generate the .docx last, once, when the content is final. The .md is the canonical artifact; the .docx is a terminal derivative.
Discipline-agnostic: coding workshop, leadership seminar, safety training, onboarding, creative workshop — all apply equally.
Voice mode: this conversation may be conducted by voice. Transcription can introduce homophones, missing punctuation, or ambiguous proper nouns (names, company names, tool names). If any answer is unclear after transcription, ask a short clarifying question before moving on — do not guess.
Reference files
Load these files at the steps indicated. Do not load them all upfront.
| File | Load at |
|---|---|
references/tone-of-voice.md |
Step 1 (after language + audience confirmed) |
references/markdown-draft.md |
Step 5 (before writing the draft) |
references/docx-generation.md |
Step 6 (before generating the .docx) |
Step 0 — Check dependencies
Before asking the user anything, verify skill availability.
docx skill (required for Step 6)
- If found: note it; load it at Step 6
- If not found: warn the user — it is required to generate the final Word document and can be installed from Anthropic's official skill library. Offer to proceed with the Markdown draft in the meantime.
Humanizer skill (recommended)
- After Step 1, look for a humanizer skill matching the chosen language
- If found: load it and apply it during the humanization pass in Step 5
- If not found: tell the user once, then fall back to inline humanization rules (Step 5b). Suggest installing a humanizer skill for the chosen language.
Step 1 — Language & audience
Ask:
- "In what language should I write the report? (French / English / other)"
- "Who is the primary reader? (executive / HR / direct management / external client / internal archive)"
Then load references/tone-of-voice.md and apply its guidance throughout.
Step 2 — Template
What ships with it
4 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.
- 1mo ago First seen · 255 lines · 179 tokens per session scan A 9c15adea5a70
training-report is a skill published in the GitHub repository hssh8917/cc-skills (2 stars, last pushed 13d ago), licensed MIT. It adds 179 tokens to every session and 2,392 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to training-report, differing in 4 lines, and is treated as a copy.
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