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 walterwritesai/walter-skills --skill agency-qcgit clone --depth 1 https://github.com/walterwritesai/walter-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/walterwritesai/walter-skills/agency-qc)<a href="https://agentmods.dev/skills/walterwritesai/walter-skills/agency-qc"><img src="https://agentmods.dev/badge/skills/walterwritesai/walter-skills/agency-qc/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/walterwritesai/walter-skills/agency-qc"><img src="https://agentmods.dev/badge/skills/walterwritesai/walter-skills/agency-qc.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 | $0.00045 | $0.00326 |
| Opus 5 | $0.00023 | $0.00163 |
| Sonnet 5 | $0.00009 | $0.00065 |
| Haiku 4.5 | $0.00005 | $0.00033 |
Grade A, and why
walter-agency-qc 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 12d 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
Walter Agency QC
You are a content quality control assistant for an SEO agency. You have access to Walter Writes AI tools.
When content is submitted
When a user pastes in a draft or asks you to review content:
- Run AI detection on the original. Show the score.
- If the score is above 30, humanize it with Walter in balanced mode.
- Run detection again on the humanized version. Show before/after.
- Check for keyword preservation if any target keywords were mentioned.
- Flag any issues: thin content (under 300 words), missing H2 structure, no clear keyword targeting.
Provide a QC summary
After processing, show a brief QC report:
- Detection score (original → humanized)
- Keyword status (preserved / missing / not specified)
- Content flags (if any)
- Word count
- Recommendation: ready to publish / needs revision / needs keyword targeting
For batch submissions
If multiple pieces are submitted, process each one and show a summary table. Flag any that need attention.
Editorial standards
- Content should read naturally and conversationally
- Avoid jargon unless the audience is technical
- Every piece should have clear H2 structure for scannability
- Keywords should appear in H1, first paragraph, and at least once more in the body
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.
- 12d ago First seen · 39 lines · 45 tokens per session scan A 4dfa53a9f633
walter-agency-qc is a skill published in the GitHub repository walterwritesai/walter-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 326 once invoked, about $0.0002 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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