hashintel

Crystallize shared understanding into a reviewable spec, or update an existing one. Use when the problem needs a written specification, when assumptions or decisions have changed, or when the user says 'write a spec'.

Lightweight triage for the ln-* skill set. Use when unsure which ln skill to use next, starting work on something new, or when the user asks for guidance on their development process.

Explore radically different module shapes before committing to one. Use when choosing an API surface, deciding what a module hides vs exposes, or when the user says 'design it twice'.

Collapse meaningful ambiguity with contrastive examples. Use when a plan/design has several plausible meanings, requirements feel vague, examples would clarify intent faster than grilling, or the user asks to disambiguate, find ambiguity, use behavioral kernels, or ask contrastive questions.

Audit code quality focusing on deep modules, naming, model hygiene, and architectural clarity. Use after a burst of development, when codebase structure needs assessment, or to make code more agent-navigable.

Refresh `memory/SPEC.md` and `memory/PLAN.md` in mature mode — restore canonical truth, archive retired plan history, delete stale derivative artifacts, and flag drift against code.

d3k assistant for debugging web apps

Implement one scoped slice using TDD red-green-refactor. Use when ready to write code for a defined slice of work, or when the user wants test-driven development.

Read and write a Petri net (SDCPN) document by Automerge URL. Use when creating, editing, or querying Petri nets — adding or removing places, transitions, arcs, color types, differential equations, and parameters.

Create and maintain an Assumption Ledger — a persistent record of assumptions, their confidence, and validation status. Use when starting a new slice, resuming work in a new context window, or when implicit assumptions risk causing drift. Tracks requirements, architecture, and implementation assumptions.

Create or update a concept capsule — the conceptual anchor for a project or feature area. Use before writing code on a new project or feature, or when terms and boundaries feel unclear. Defines glossary, invariants, happy-path scenario, and non-goals.

Write a tracer-bullet card — a precise specification for one thin end-to-end slice of work. Use when scoping a new slice, defining what to build next, or breaking a feature into provable increments. Covers target behavior, boundary crossings, risks, and definition of done.

Create characterization tests (Golden Master) for existing code so you can refactor or replace safely. Use before refactoring, strangler-replacing, or modifying code with unclear behavior. Captures observable behavior with a minimal harness, producing tests, fixtures, and a coverage report.

Methodology triage consultant for tracer-bullet development. Use when unsure which pragma skill to run next, when starting a new project, or when the current approach feels stuck. Interviews the user, assesses state, and recommends the next pragma skill.

Turn capsule invariants and boundary crossings into executable contracts. Use after creating a concept capsule, or when invariants need to be enforced in code. Covers preconditions, postconditions, constructor validation, domain types, and contract tests.

Design feedback loops and validation harnesses before starting implementation. Use when beginning any non-trivial development task, when the agent can't easily validate its own work, or when asked to set up a development harness, playground, or experiment infrastructure. Triggers on: how will I test this, set up a feedback loop, make this feedback loopable, build a harness, create a playground.

Use when creating, moving, splitting, or organizing TypeScript files and folders. Applies fractal tree file-structuring rules which reduce the cognitive overhead of choosing where to put files and ultimately navigating a codebase (once the structure is established and understood).

HashQL testing strategies including compiletest (UI tests), unit tests, and snapshot tests. Use when writing tests for HashQL code, using //~ annotations, running --bless, debugging test failures, or choosing the right testing approach.

Rust documentation practices for HASH codebase. Use when writing doc comments, documenting functions/types/traits/modules, creating error sections, using intra-doc links, or following rustdoc conventions.

HASH error handling patterns using error-stack crate. Use when working with Result types, Report types, defining custom errors, propagating errors with change_context, adding context with attach, implementing Error trait, or documenting error conditions in Rust code.

Guide for creating effective Agent Skills. Use when users want to create a new skill (or update an existing skill) that extends an AI agent's capabilities with specialized knowledge, workflows, or tool integrations. Covers skill structure, YAML frontmatter, trigger configuration, and the 500-line rule.

HashQL diagnostic writing patterns using hashql-diagnostics crate. Use when creating error messages, warnings, Labels, Messages, Severity levels, Patches, Suggestions, or improving diagnostic quality in HashQL code.

HashQL J-Expr syntax for writing queries. Use when writing J-Expr code, using #literal/#struct/#list constructs, understanding function call syntax, or working with HashQL query files (.jsonc).

Generate Rust documentation to understand crate APIs, structure, and usage. Use when exploring Rust code, understanding crate organization, finding functions/types/traits, or needing context about a Rust package in the HASH workspace.