engineering/grill-with-docs/skills/grill-with-docs/SKILL.md
Docs-anchored grilling session — challenges a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), and updates those files inline as terminology and decisions crystallise. Use when user wants to stress-test a plan against documented domain language, or mentions "grill with docs".
npx skillsauth add alirezarezvani/claude-skills grill-with-docsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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<what-to-do>Derived from Matt Pocock's grill-with-docs (MIT, © 2026 Matt Pocock). Matt's interview discipline + docs-anchored grilling rules preserved verbatim under MIT. Additions in this repo: 3 stdlib validators (CONTEXT.md linter, ADR scanner, glossary↔code consistency check), 3 in-depth references each citing 7+ authoritative sources,
cs-grill-with-docsagent,/cs:grill-with-docscommand. See Wrapper additions below.
Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time, waiting for feedback on each question before continuing.
If a question can be answered by exploring the codebase, explore the codebase instead.
</what-to-do> <supporting-info>During codebase exploration, also look for existing documentation:
Most repos have a single context:
/
├── CONTEXT.md
├── docs/
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
If a CONTEXT-MAP.md exists at the root, the repo has multiple contexts. The map points to where each one lives:
/
├── CONTEXT-MAP.md
├── docs/
│ └── adr/ ← system-wide decisions
├── src/
│ ├── ordering/
│ │ ├── CONTEXT.md
│ │ └── docs/adr/ ← context-specific decisions
│ └── billing/
│ ├── CONTEXT.md
│ └── docs/adr/
Create files lazily — only when you have something to write. If no CONTEXT.md exists, create one when the first term is resolved. If no docs/adr/ exists, create it when the first ADR is needed.
When the user uses a term that conflicts with the existing language in CONTEXT.md, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account' — do you mean the Customer or the User? Those are different things."
When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.
When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?"
When a term is resolved, update CONTEXT.md right there. Don't batch these up — capture them as they happen. Use the format in CONTEXT-FORMAT.md.
CONTEXT.md should be totally devoid of implementation details. Do not treat CONTEXT.md as a spec, a scratch pad, or a repository for implementation decisions. It is a glossary and nothing else.
Only offer to create an ADR when all three are true:
If any of the three is missing, skip the ADR. Use the format in ADR-FORMAT.md.
</supporting-info>The additions below are not part of Matt's upstream skill. They operationalize the upstream's rules into deterministic, stdlib-only validators that pair naturally with the interview loop.
Pre-flight (before the first question):
scripts/context_md_linter.py CONTEXT.md if a CONTEXT.md exists — confirms the glossary is well-formed before grilling against it.scripts/adr_scanner.py docs/adr/ if docs/adr/ exists — surfaces numbering gaps, malformed ADRs, status-frontmatter inconsistencies.scripts/glossary_code_consistency.py --context CONTEXT.md --code src/ — flags defined-but-unused terms (dead glossary) and code-only common nouns that may need definitions. Use these flags as opening grill questions.During the session (Matt's rules apply):
CONTEXT.md immediately; re-run context_md_linter.py if the edit is structural.docs/adr/; re-run adr_scanner.py to confirm numbering.Closing:
glossary_code_consistency.py run to confirm no new orphan terms were introduced.| Tool | One-line role |
|---|---|
| scripts/context_md_linter.py | Validate CONTEXT.md against the CONTEXT-FORMAT.md structure. PASS/WARN/FAIL per rule. |
| scripts/adr_scanner.py | Walk docs/adr/, check NNNN-slug.md pattern, numbering integrity, body completeness. |
| scripts/glossary_code_consistency.py | Cross-reference bold terms in CONTEXT.md against codebase usage. Flag dead glossary + code-only common nouns. |
references/ubiquitous_language.md — why a glossary belongs in source control (Evans, Vernon, Khononov, Wlaschin, Brandolini, Avram & Marinescu, Fowler)references/adr_practice.md — when an ADR earns its keep (Nygard, Tyree & Akerman, Zimmermann Y-statements, MADR, ThoughtWorks Radar, adr-tools, Backstage)references/context_md_as_artifact.md — CONTEXT.md as living artifact (Khononov on language drift, Kernighan on naming, BoundedContext bliki, Confluent on data contracts, Brandolini on EventStorming glossary)cs-grill-with-docs (see ../../agents/cs-grill-with-docs.md)/cs:grill-with-docs (see ../../commands/cs-grill-with-docs.md)Version: 1.0.0 Derived: Matt Pocock's grill-with-docs (MIT) + this repo's wrapper
tools
Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.
tools
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
development
Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).
development
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.