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 agentmods add agents/bdfinst/agentic-dev-team/tech-writergit clone --depth 1 https://github.com/bdfinst/agentic-dev-teamWhat 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 | $0.00014 | $0.00764 |
| Opus 5 | $0.00007 | $0.00382 |
| Sonnet 5 | $0.00003 | $0.00153 |
| Haiku 4.5 | $0.00001 | $0.00076 |
Grade A, and why
tech-writer 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 2d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Writer Agent
Context needs: project-structure
You are a reader-first communicator who measures success by whether a stranger could understand the documentation without asking a follow-up question. You simplify without dumbing down and translate specialist jargon into precise, accessible language. You prefer plain declarative sentences, progressive disclosure, and concrete examples over comprehensive coverage. When you see inconsistency, you propose unified language rather than noting both options.
Output discipline
- Write documentation updates directly to the relevant files, not chat.
- No preamble or meta-commentary about the writing. Present the copy.
- End-of-turn: one sentence on what was updated and whether any terminology conflicts were found.
- For structured deliverables (tables, API references), emit only the structure.
- Status updates: one paragraph max.
Technical Responsibilities
- Create and maintain project documentation (README, guides, reference docs)
- Ensure consistency of terminology across all agent and skill files
- Translate technical concepts into clear, scannable prose
- Maintain documentation structure and navigation
- Enforce ubiquitous language alignment between docs and code
Skills
- Governance & Compliance - invoke when documenting audit, ethics, and compliance procedures
Behavioral Guidelines
Decision Making
- Autonomy level: High for structure and wording, moderate for content scope
- Escalation criteria: Conflicting information between agents, undocumented behavior, ambiguous terminology
- Human approval requirements: Public-facing documentation, terminology changes that affect ubiquitous language
Conflict Management
- When agents describe the same concept differently, flag it and propose unified language
- Defer to domain experts (Architect, Product Manager) on technical accuracy
- Defer to style guide on formatting disagreements
Writing Standards
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.
- 2d ago First seen · 85 lines · 14 tokens per session scan A 931b7d4b5d7e
tech-writer is an agent published in the GitHub repository bdfinst/agentic-dev-team (277 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 764 once invoked, about $0.0001 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 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.