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 ahkedia/lyra-ai --skill content-revisiongit clone --depth 1 https://github.com/ahkedia/lyra-aiWrote 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/ahkedia/lyra-ai/content-revision)<a href="https://agentmods.dev/skills/ahkedia/lyra-ai/content-revision"><img src="https://agentmods.dev/badge/skills/ahkedia/lyra-ai/content-revision/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/ahkedia/lyra-ai/content-revision"><img src="https://agentmods.dev/badge/skills/ahkedia/lyra-ai/content-revision.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 | $0.00038 | $0.00248 |
| Opus 5 | $0.00019 | $0.00124 |
| Sonnet 5 | $0.00008 | $0.00050 |
| Haiku 4.5 | $0.00004 | $0.00025 |
Grade A, and why
content-revision 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 10d 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
Content Revision
Trigger: Akash replied to your draft with changes, tone notes, or “make it shorter,” etc.
Rules
-
Full pass, not a patch. Re-emit the full text. Apply his feedback and re-check:
- Voice Canon (Personal Wiki → Type = Voice Canon; fetch blocks)
- Channel constraints (length, format, platform) stated at the start of the task
voice-system/NEGATIVE_STYLE.mdpatterns to avoid (if drafting X/long-form in repo context)
-
Do not drop context. If the thread already contains metrics, names, or links, keep them — do not ask again.
-
Notion path:
MEMORY.md→ Personal Wiki database_id + query Voice Canon first, then Career/domain pages as needed.
If you only apply the feedback bullets and the piece drifts toward generic voice, you failed the skill — start over with Voice Canon loaded.
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.
- 10d ago First seen · 22 lines · 38 tokens per session scan A 2afee34e0f23
content-revision is a skill published in the GitHub repository ahkedia/lyra-ai (5 stars, last pushed 21d ago), licensed MIT. It adds 38 tokens to every session and 248 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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