docs-improve

A guide for thoroughly improving a Markdown documentation file. It covers missing information, incorrect or broken content, organization, links, and formatting.

In plain words
What is it for?
Use it to review a documentation file, plan changes, add needed sections, correct inaccuracies, and reorganize content.
Why use it?
It helps turn documentation that is thin, confusing, or outdated into a clearer and more complete reference. It also keeps the document aligned with its intended purpose.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/deephaven/deephaven-mcp/docs-improve
Any agent
npx skills add deephaven/deephaven-mcp --skill docs-improve
Clone the repo
git clone --depth 1 https://github.com/deephaven/deephaven-mcp

Made for: Claude Code, Codex.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 571 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.00571
Opus 5 $0.00032 $0.00285
Sonnet 5 $0.00013 $0.00114
Haiku 4.5 $0.00006 $0.00057

Measured 2d ago against content hash c7752e2f6945, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

docs-improve 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.

.agents/skills/docs-improve/SKILL.md · 28 lines

How it starts

The opening of the file, as written. The whole thing — 28 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to use this vs. docs-accuracy: use docs-improve for a full review (accuracy + reorganization + missing content + formatting). Use docs-accuracy for surgical correctness-only fixes when the doc's structure is already sound.

Before doing anything

Load ref-documentation-roles — the canonical source for each document's role and the editing rules that follow from it (in-scope content stays; out-of-scope content relocates rather than being rewritten in place; self-contained vs. generic docs; the cross-reference policy). Evaluate every proposed change against the target document's role; if a change would violate it, stop and reconsider before editing.

Steps

Create a plan for improving this markdown file, then execute it.

  1. Confirm the document's role per ref-documentation-roles. Note any sections currently out of scope; plan to relocate them, not rewrite them in place.
  2. Look for content that is missing from this file for its role and needs to be added. Use the source code as a reference. If there is a conflict, the source code should be believed over the markdown.
  3. Apply the docs-accuracy skill.
  4. Draft the target section outline for this document's role: one section per in-scope responsibility, ordered along the reader's path through the task. Produce the outline as an explicit list before editing.
  5. Reorganize the sections to match the outline from step 4; every section's content stays within the document's role.
  6. Make sure that all referenced files and paths have hyperlinks.
  7. Check all of the links in the document to make sure they are correct.
  8. Link every product, website, or service the document references to its canonical URL.
  9. Apply the ref-markdown-documentation-standards skill for formatting compliance (including the Table of Contents requirement).
  10. Final residual-check pass. Walk the document end-to-end one more time against the role from step 1; list any remaining bullets where you can name a concrete defect (out-of-scope content, missing example, broken link, stale fact, ambiguous instruction). If you cannot name a concrete defect, the doc is done — stop. Vague "could be improved" feelings are not findings.

Read the full file on GitHub · 28 lines

Changes

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.

  1. 2d ago First seen · 28 lines · 65 tokens per session scan A c7752e2f6945

Subscribe to this mod's changes

docs-improve is a skill published in the GitHub repository deephaven/deephaven-mcp (5 stars, last pushed 5d ago), licensed Apache-2.0. It adds 65 tokens to every session and 571 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

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.

obra/superpowers · 37 tokens

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.

microsoft/vscode · 62 tokens

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.

microsoft/vscode · 51 tokens

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.

microsoft/vscode · 53 tokens

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…

microsoft/vscode · 71 tokens