Borrowing it
Nothing to install: this file belongs to dork-labs/dorkos. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dork-labs/dorkos/main/.agents/skills/writing-developer-guides/SKILL.mdgit clone --depth 1 https://github.com/dork-labs/dorkosWrote 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/dork-labs/dorkos/writing-developer-guides)<a href="https://agentmods.dev/skills/dork-labs/dorkos/writing-developer-guides"><img src="https://agentmods.dev/badge/skills/dork-labs/dorkos/writing-developer-guides.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.01167 |
| Opus 5 | $0.00018 | $0.00583 |
| Sonnet 5 | $0.00007 | $0.00233 |
| Haiku 4.5 | $0.00004 | $0.00117 |
Grade A, and why
writing-developer-guides 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 7d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Developer Guides
Overview
This skill teaches how to write developer guides that work well for both AI coding agents and human developers. The key insight: AI agents need fast context retrieval, clear decision support, and copy-paste ready patterns.
When to Apply
- Creating a new file in
contributing/ - Updating or refactoring an existing guide
- Reviewing guides for completeness
- User asks about documentation structure
Core Principle
Structure for retrieval, not teaching.
Traditional documentation assumes sequential reading. AI agents retrieve specific information based on task context. Every section should be independently useful.
Required Sections (In Order)
Each developer guide must include these sections in this sequence:
1. Title + Overview (2-3 sentences)
# [Topic] Guide
## Overview
[What this guide covers] and [why it matters for this project].
Why this order: AI agents use the overview to determine relevance before reading further.
2. Key Files Table
## Key Files
| Concept | Location |
| ------------- | -------------------- |
| Configuration | `src/path/config.ts` |
| Types | `src/path/types.ts` |
Why early: Agents need to know WHERE before HOW. This prevents searching.
3. Decision Matrix ("When to Use What")
## When to Use What
| Scenario | Approach | Why |
| -------- | -------- | --------- |
| Need X | Use Y | Because Z |
| Need A | Use B | Because C |
Critical for AI: A good decision matrix eliminates 80% of clarifying questions. Agents can pattern-match their current task to the right approach.
4. Core Patterns (Code Examples)
## Core Patterns
### [Pattern Name]
[1-2 sentence context]
```typescript
// Complete, runnable example
// Comments explain WHY, not WHAT
export function example() {
// This pattern ensures X because Y
return result;
}
```
**Requirements:**
- Examples must be complete (copy-paste ready)
- Include imports if non-obvious
- Comments explain reasoning, not mechanics
### 5. Anti-Patterns
```markdown
What ships with it
1 file 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.
- 7d ago First seen · 200 lines · 36 tokens per session scan A 783e8e94b95b
writing-developer-guides is a skill published in the GitHub repository dork-labs/dorkos (9 stars, last pushed yesterday), licensed MIT. It adds 36 tokens to every session and 1,167 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.
Other skills, from other repositories
hive.slack-notifications-setup
Set up a Slack notification channel (Sentinel) for a colony by driving the browser — reuse or create the "Hive Sentinel" Slack app from a JSON manifest, install it, capture the bot + app tokens, create/select the channel via the Slack API, and turn Sentinel on so the colony can ping the user on Slack and accept…
hive.pdf
Read, write, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python (pypdf, pdfplumber, reportlab, pypdfium2) and command-line tools (poppler-utils, qpdf). Use when the user asks to extract text/tables/images from a PDF, create or modify a PDF, combine or split PDFs, OCR a scanned PDF…
hive.note-taking
Maintain a free-form scratchpad of decisions, extracted values, and open questions so context pruning doesn't lose anything you still need.
sdlc-accelerate
End-to-end SDLC ramp-up from idea to construction-ready with automated phase transitions.
ralph-memory
Manage Al semantic memory entries — list, query, and clear lessons learned across loop iterations.
project-awareness
Detect project type, AIWG framework state, team configuration, and active work to summarize status and recommend next actions.