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 phazonoverload/devadvokit --skill turn-incident-into-contentgit clone --depth 1 https://github.com/phazonoverload/devadvokitWrote 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/phazonoverload/devadvokit/turn-incident-into-content)<a href="https://agentmods.dev/skills/phazonoverload/devadvokit/turn-incident-into-content"><img src="https://agentmods.dev/badge/skills/phazonoverload/devadvokit/turn-incident-into-content/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/phazonoverload/devadvokit/turn-incident-into-content"><img src="https://agentmods.dev/badge/skills/phazonoverload/devadvokit/turn-incident-into-content.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 | $0.00067 | $0.01051 |
| Opus 5.5 | $0.00027 | $0.00420 |
| Sonnet 5.5 | $0.00013 | $0.00210 |
| Haiku 4.5 | $0.00007 | $0.00105 |
Grade A, and why
turn-incident-into-content 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 2mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before doing anything else:
- Check if
~/.devadvokit.mdexists. - If it does, read it silently and use it throughout this skill.
- If it does not, stop and tell the user: "I need your DevRel context before I can run this skill. Please run /setup-devadvokit first."
What NOT to Do
This skill produces content directions — not finished publication drafts. Specifically:
- No polished blog posts — you're creating frameworks for future pieces
- No commit-ready docs PRs — this gives you the structure and says where docs should be updated, not the PR text itself
- No social media threads — use
/repurpose-talkfor that workflow
The goal is extracting the reusable lesson from a specific incident.
Q&A
Ask these questions one at a time. Wait for each answer before asking the next.
-
What was the problem? Describe what the user was trying to do and what they ran into. Be specific — the actual error message, the unexpected behavior, what was confusing.
-
What did you try? Walk me through your debugging process. What solutions did you attempt? What didn't work? This shows the problem-solving journey.
-
What actually worked? What solved it? Be specific — the command, the config change, the conceptual shift, whatever fixed it.
-
What would you tell someone hitting this cold? If you were writing a guide for someone encountering this for the first time, what's the one-sentence takeaway they need?
-
Who was the user? (Developer, data scientist, DevRel peer, etc. — this affects audience framing)
Output
Produce all of the following once the Q&A is complete.
1. TIL Format
A short-form "Today I Learned" version suitable for a quick post, thread, or newsletter item.
Title: [Working title with "TIL" framing]
Body: 2–3 sentences. Start with what didn't work, then the solution, then the takeaway. Keep it punchy.
Format fit: Micro-post, thread starter, or newsletter TIL section.
2. Full Context Format
A longer framework for a blog post or deep-dive content.
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.
- 2mo ago First seen · 110 lines · 67 tokens per session scan A a1b0f23fc617
turn-incident-into-content is a skill published in the GitHub repository phazonoverload/devadvokit (16 stars, last pushed 7mo ago), licensed MIT. It adds 67 tokens to every session and 1,051 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
turn-incident-into-content compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| turn-incident-into-contentphazonoverload/devadvokit | Skill | 16 | 7mo ago | MIT | A | 67 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |