Imported from projectious-work/aibox (context/templates/processkit/v0.26.16/context/skills/processkit/skill-finder/SKILL.md). Install upstream with npx skills add projectious-work/aibox --skill skill-finder. Copyright stays with the author.

Skill Finder

Intro

When you are unsure which skill to use, start here. This skill maps what the user is asking for to the skill that handles it. It is not a skill you invoke to do work — it is a skill you read to decide what to invoke next.

Overview

By trigger phrase

Find the phrase that most closely matches what the user said, then load that skill before proceeding.

By directory (physical layout)

Skills are organized into 7 category subdirectories on disk. Use the directory name as the category: value when authoring or filtering:

By category

A curated selection of the most commonly used skills per task domain. For the full catalog, read skills/INDEX.md.

Process

• task-router — primary routing entry point: maps task to skill + process override + MCP tool
• workitem-management — create, transition, and query WorkItems
• decision-record — capture architectural and product decisions as DecisionRecords
• artifact-management — register and retrieve completed deliverables
• event-log — write auditable log entries for any project event
• note-management — capture, review, and promote fleeting ideas and insights
• session-handover — write an end-of-session handover before shutdown
• standup-context — write a standup update (done / doing / next / blockers)
• status-briefing — generate a session-start orientation from project state
• context-grooming — periodically prune and compact the project context
• runtime-prune — inspect and invoke safe cleanup for runtime-manager-owned state
• release-semver — plan and execute a semver release
• retrospective — post-release blameless retrospective (4 signals, dual-emit Artifact+LogEntry)

Architecture

• software-architecture — high-level system design patterns and trade-offs
• system-design — designing systems from requirements to components
• api-design — REST, RPC, and event-based API contracts
• domain-driven-design — bounded contexts, aggregates, ubiquitous language
• software-modularization — module and package boundary design
• microservice-creation — service extraction, communication patterns, orchestration
• event-driven-architecture — pub-sub, event sourcing, CQRS

Code quality

• code-review — reviewing diffs and PRs for correctness, style, and risk
• refactoring — safe, incremental refactoring strategies
• tdd-workflow — test-first development cycle
• testing-strategy — choosing the right test types and coverage targets
• debugging — systematic bug investigation and root-cause analysis
• error-handling — error propagation, recovery, and user-facing messages

Security

• secure-coding — OWASP top 10, input validation, output encoding
• threat-modeling — STRIDE analysis and risk prioritisation
• secret-management — credential storage, rotation, and injection
• auth-patterns — authentication and authorization patterns

Infrastructure

• ci-cd-setup — pipeline design and configuration
• dockerfile-review — image hardening, layer optimisation, multi-stage builds
• kubernetes-basics — Deployments, Services, ConfigMaps, autoscaling
• terraform-basics — resource definitions, state management, modules

Observability

• logging-strategy — structured logging, levels, and retention
• metrics-monitoring — metric types, dashboards, SLOs
• distributed-tracing — trace propagation, span design, sampling
• incident-response — triage, mitigation, and communication during incidents

Data and AI

• rag-engineering — retrieval-augmented generation pipelines
• prompt-engineering — prompt design, few-shot examples, chain-of-thought
• llm-evaluation — benchmarking and red-teaming language models
• model-recommender — pick the right AI model via spider-chart profiles and task-plan routing
• data-pipeline — ETL/ELT design and orchestration
• pandas-polars — dataframe operations and transformations

Document creation

• docx-authoring — python-docx for Word documents
• pptx-authoring — python-pptx for presentations
• xlsx-modeling — openpyxl for spreadsheets and financial models
• pdf-workflow — WeasyPrint / ReportLab / pypdf for PDF generation

Role-specific

• prd-writing — product requirements documents
• user-research — interview guides, synthesis, personas
• data-storytelling — turning analysis into decisions for non-technical audiences
• legal-review — pre-consultation contract and compliance review
• email-drafter — professional email drafting with copy-paste output

Meta

• skill-builder — design and author new processkit skills, including library expert recipe skills
• skill-reviewer — review a skill against the processkit standard
• research-with-confidence — structured research with explicit confidence labels
• devils-advocate — adversarial analysis of a plan or proposal
• board-of-advisors — multi-perspective simulation with named advisor archetypes
• status-briefing — session-start orientation (also listed under Process)

How to use a skill

Once you have identified the right skill:

1. Read the skill's SKILL.md — start with the Intro (3 sentences) to confirm it is the right match. If yes, read Overview for the workflow.
2. Follow the skill's instructions, adapting to the project's specific context.
3. Use Full reference only for edge cases or field-by-field specs.
4. If the skill has an MCP server (mcp/SERVER.md), its tools are available as function calls — the skill's Overview section describes when to use them.

If no skill in this index matches, check skills/INDEX.md for the full catalog, or use skill-builder to author a new skill for the gap.

Catalog queries

The catalog MCP tool provides user-facing skill discovery. Use it when the user wants to browse, filter, or export the skill roster rather than find a specific skill for a task.

Trigger phrases

Tool signature

def catalog(
    category: str | None = None,
    tag: str | None = None,
    keyword: str | None = None,
    columns: list[str] | None = None,
    sort_by: str | None = None,
    output: str = "markdown",  # "markdown" | "json" | "yaml"
) -> str | list[dict]

Defaults: all skills, columns=["name","category","description"], sort_by="name", output="markdown".

Available columns:

Example invocations

1. Default — all skills as a Markdown table (name, category, description)

catalog()

Returns a Markdown table with ~130+ rows, sorted by name. Shape: str (Markdown table).

2. Filter by category, JSON output

catalog(category="processkit", output="json")

Returns only processkit-category skills as a JSON array. Shape: list[dict] — e.g. [{"name": "artifact-management", "category": "processkit", "description": "Register and retrieve completed deliverables."}, …]

3. Keyword search, restricted columns

catalog(keyword="model", columns=["name", "category", "description"])

Returns all skills whose name or description contains "model" (case-insensitive). Shape: str (Markdown table).

4. Custom columns with YAML output

catalog(columns=["name", "layer", "has_mcp"], output="yaml")

Returns a YAML fenced code block listing name, layer, and has_mcp for every skill, sorted by name.

5. Tag filter

catalog(tag="routing", columns=["name", "category", "tags"])

Filters to skills that carry "routing" in their frontmatter tags list (exact match, case-insensitive).

Gotchas

• Loading this skill every time instead of once. skill-finder is an orientation aid, not a workflow skill. Read it once to identify the right skill, then load that skill and work from it. Do not keep skill-finder loaded alongside the working skill — it consumes context without adding value once you have identified the skill to use.
• Treating the trigger-phrase table as exhaustive. The table maps common phrases; it is not a complete index of all 120+ skills. If no phrase matches, scan the by-category section or read skills/INDEX.md. If the task is genuinely novel, use skill-builder to create a skill for it.
• Skipping skill-finder when the task is "obvious." The most common mistake is loading a skill by name from memory and discovering mid-task that the skill does not quite fit. Thirty seconds with the trigger-phrase table prevents an incorrect skill invocation. Default to checking even for familiar task types.
• Using the category labels to filter instead of the trigger phrases. The categories help humans browse; agents should match on trigger phrases, not category names. "Code quality" does not tell you whether to load code-review, refactoring, or tdd-workflow — the trigger phrase does.
• Not updating skill-finder when new skills are added. When a new skill is added to the catalog, add its trigger phrases to the table and its one-liner to the appropriate category. skill-finder is only reliable if it is kept current. The skill-builder skill includes a reminder to update this index.
• Confusing skill-finder with skill-builder. skill-finder helps you find an existing skill. skill-builder helps you create a new one. If skill-finder returns no match, the correct next step is skill-builder, not a general-purpose attempt to solve the task without a skill.
• Ignoring the core: true intent when customising skill packages. Until aibox enforces core: true in the install pipeline, project owners who configure [skills].include must add skill-finder explicitly. Omitting it means agents lose the navigation aid exactly when the catalog is most customised and therefore hardest to navigate.

Full reference

The core: true flag

The core: true field in this skill's frontmatter is a proposed convention. It signals intent: this skill should be installed unconditionally, regardless of [skills].include or [skills].exclude configuration in aibox.toml.

Current status: the flag is present in the frontmatter as documentation. aibox does not yet enforce it — a companion aibox issue will land the content_install.rs change. Until then, project owners must include skill-finder in any explicit [skills].include list.

Why it matters: a project owner who limits the installed skills to a curated subset has, by definition, the most non-obvious skill catalog. That is precisely when skill-finder is most needed. A skill that can be excluded provides weaker guarantees than one that cannot.

Keeping this index current

When adding a new skill to processkit:

1. Add 1–3 trigger phrases to the trigger-phrase table
2. Add a one-liner under the appropriate category in the by-category section
3. If no existing category fits, add a new category

The skill-builder skill includes a step reminding the author to update skill-finder. The skill-reviewer skill checks that skill-finder has been updated.