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 skills/shareai-lab/kode-cli/doc-coauthoringnpx skills add shareAI-lab/Kode-CLI --skill doc-coauthoringgit clone --depth 1 https://github.com/shareAI-lab/Kode-CLIWhat 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 | $0.00074 | $0.00882 |
| Opus 5 | $0.00037 | $0.00441 |
| Sonnet 5 | $0.00015 | $0.00176 |
| Haiku 4.5 | $0.00007 | $0.00088 |
Grade A, and why
doc-coauthoring 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 3d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doc Co-Authoring
Turn partial context into a clear document by following a staged workflow. Keep the user in control of decisions, and optimize for a doc that works for readers who do not share the author’s context.
Triggers
Use this workflow when the user asks to:
- write or refine documentation, proposals, RFCs, PRDs, decision docs, specs
- “summarize our discussion into a doc”
- “make this readable for others” / “share with the team”
- create a template or standard for recurring documents
If the user explicitly wants freeform writing, keep the workflow lightweight (ask fewer questions; draft faster).
The Workflow (3 stages)
Stage 1 — Context Capture (close the gap)
Goal: collect the minimum context required to write a doc that is correct, scoped, and actionable.
Ask for:
- Doc type + goal: what is this document for, and what decision/action should it unlock?
- Audience: who will read it, and what do they already know?
- Constraints: deadlines, non-goals, dependencies, security/compliance, platform limits.
- Current state: what exists today? what’s broken? what’s missing?
- Options considered: at least 1–2 alternatives and why they may/ may not work.
- Success criteria: how we know it worked (metrics, user outcomes, acceptance tests).
- Open questions: unknowns that block writing certain sections.
Output of Stage 1:
- a short “context snapshot”
- a list of open questions (ranked by importance)
- a proposed doc outline (1 screen)
Stage 2 — Outline-First Drafting (iterate by section)
Goal: draft a document in layers without losing coherence.
Rules:
- Outline before prose. Do not write full paragraphs until the outline is agreed.
- One section at a time. Draft → review → revise, then move on.
- Maintain a decision log (small bullet list) so changes are explicit.
- Keep unknowns visible: unresolved items stay in an “Open Questions / Risks” section, not hidden.
Recommended iteration loop per section:
What ships with it
2 files 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.
- 3d ago First seen · 98 lines · 74 tokens per session scan A 2a22125f8344
doc-coauthoring is a skill published in the GitHub repository shareAI-lab/Kode-CLI (5,212 stars, last pushed 6d ago), licensed Apache-2.0. It adds 74 tokens to every session and 882 once invoked, about $0.0004 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…