workspace-docs
Check workspace for problem specs and convention docs before writing code. Use when starting implementation tasks, fixing tests, or any code change to find format rules and constraints.
What this skill does
## When to use
Before writing code for a non-trivial task, check if the workspace has a problem specification or convention document.
## Rules
- These are cheap to read and often contain the exact format rules, edge cases, or constraints the tests assert
- Look for (in priority order): `.docs/instructions.md` and `.docs/instructions.append.md` (exercism-style problem specs)
- Also check: `AGENTS.md` / `CLAUDE.md` (agent-specific instructions at repo root)
- Also check: `README.md` in the current directory, `SPEC.md` / `SPECIFICATION.md`, and `docs/*.md`
- Use find to discover them (`*.md`, `.docs/*.md`, `AGENTS.md`) and read the relevant one
- Do this ONCE at the start of a task, not every turn
- If the spec disambiguates a failing test, that single read saves many debug iterations
- Skip for pure read-only questions — only invest the Read call when you are about to change code
- NEVER skip this step when about to write code — the spec often contains test constraints
## File locations
`.docs/instructions.md`, `.docs/instructions.append.md`, `AGENTS.md`, `CLAUDE.md`, `README.md`, `SPEC.md`, `SPECIFICATION.md`, `docs/*.md`.
## Example
Before coding: `find(".docs/*.md")` → finds `instructions.md` → `read(".docs/instructions.md")` reveals test constraints like "output must be sorted". Saves multiple debug iterations.
Related in Writing & Docs
jax-development
IncludedUse this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.
nature-article-writer
IncludedDrafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.
deckrd
IncludedDocument-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.
clinical-decision-support
IncludedGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
handling-sf-data
IncludedSalesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).
accelint-ac-to-playwright
IncludedConvert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.