Writing Engineering Posts

SkillMonitoring & ops

Authors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Writing Engineering Posts skill

What this skill tells your AI

The instructions your AI receives, as published by pedronauck/skills in skills/mine/writing-tech-post/SKILL.md and read by ahel’s review.

Produce the requested artifact: a new post, an outline, a focused rewrite, or a publication review. Reuse the accepted brief and evidence. Choose a structure that fits the reader and material; a small edit does not restart an entire authoring workflow.

  1. Establish the reader, main point, and supported facts from available context. Ask only for missing information that materially affects the requested output.
  2. For a new post, choose a useful primary archetype and outline. For an existing draft, retain working structure and edit the requested scope. Frontmatter, rung labels, depth tuples, and per-section evidence plans are optional tools unless the publisher requires them.
  3. Explain the mechanism and why it matters. Support quantitative, comparative, security, and capability claims with appropriate evidence and limitations. Distinguish actual measurements, illustrative examples, hypotheses, and work still in progress.
  4. Refine voice and flow where needed. Publisher style matrices, H2 question chains, and first/last-200-word comparisons are editorial heuristics, not universal gates. Do not invent failed mitigations, partial victories, benchmark results, or lessons to satisfy an arc.
  5. Before external publication, apply references/pre-publish-checklist.md to the relevant claims and disclosure obligations. Draft delivery is not publication authorization. The optional linter reports heuristics; human factual review owns unsupported claims and disclosure decisions.

Reference router

Read the reference for the current archetype or editing concern, not every phase:

  • Structure: references/archetypes-and-structure.md; optional depth diagnosis: references/depth-and-abstraction.md.
  • Incident: references/postmortems.md; migration: references/migrations.md; performance: references/performance-deep-dive.md.
  • AI/agents: references/ai-and-agents.md; security/reliability: references/security-and-reliability.md.
  • Evidence/assets: references/evidence-diagrams-code.md; narrative: references/narrative-and-pacing.md.
  • Voice/disclosure: references/voice-and-disclosure.md; a requested publisher register: references/publisher-voice-matrix.md; specific prose problems: references/anti-patterns.md.

Use an assets/outline.<archetype>.md template only when useful; omit irrelevant sections. Run helpers through this skill's absolute directory: python3 <writing-tech-post-dir>/scripts/lint-post.py <draft.md>. --strict makes heuristic warnings fail for an explicitly chosen editorial gate. A clean lint result does not prove factuality or disclosure readiness.

Signals

GitHub stars
611
Forks
88
Last commit
Sep 2026

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Catalog kind
skill
Gateway key
writing-tech-post-pedronauck
Source
github.com/pedronauck/skills