skill-recommender

Intelligent skill suggestion engine that analyzes user intent and project context to recommend appropriate documentation skills

$ Installer

git clone https://github.com/vladm3105/aidoc-flow-framework /tmp/aidoc-flow-framework && cp -r /tmp/aidoc-flow-framework/.claude/skills/skill-recommender ~/.claude/skills/aidoc-flow-framework

// tip: Run this command in your terminal to install the skill


title: "skill-recommender: Intelligent skill suggestion engine for documentation tasks" name: skill-recommender description: Intelligent skill suggestion engine that analyzes user intent and project context to recommend appropriate documentation skills tags:

  • sdd-workflow
  • ai-assistant
  • utility
  • shared-architecture custom_fields: layer: null artifact_type: null architecture_approaches: [ai-agent-based] priority: primary development_status: active skill_category: utility upstream_artifacts: [PRD-00, ADR-000] downstream_artifacts: []

skill-recommender

Purpose

Analyze user requests and recommend appropriate documentation skills from the AI Dev Flow framework catalog.

Problem Solved: Users must know which of 25+ skills to invoke for their documentation task, requiring deep framework knowledge.

Solution: Parse user intent, match against skill catalog, and provide ranked recommendations with confidence scores and rationale.

When to Use This Skill

Use skill-recommender when:

  • User is unsure which skill to use for a documentation task
  • Starting a new documentation workflow and need guidance
  • Want to discover available skills for a specific intent
  • Need help navigating the skill catalog

Do NOT use when:

  • User explicitly requests a specific skill (e.g., "/skill doc-prd")
  • Performing non-documentation tasks
  • User is experienced and knows the target skill

Skill Inputs

InputTypeRequiredDescription
user_requeststringYesNatural language description of what user wants to do
project_contextobjectNoProject structure and existing artifacts (from context-analyzer)
max_recommendationsnumberNoMaximum recommendations to return (default: 3)

Skill Workflow

Step 1: Parse User Intent

Extract action verbs and targets from the user request:

Intent Categories:

CategorySignal KeywordsExample Request
createcreate, write, draft, new, add"Create a new PRD for user authentication"
updateupdate, modify, edit, change, revise"Update the traceability section of SPEC-01"
validatevalidate, check, verify, audit, review"Check if my artifacts have proper traceability"
analyzeanalyze, review, examine, inspect"Analyze the project documentation structure"
planplan, roadmap, schedule, organize"Create an implementation roadmap from ADRs"

Target Extraction:

TargetSignal KeywordsMaps To
business requirementsbusiness, brd, objectivesdoc-brd
product requirementsproduct, prd, features, user storiesdoc-prd
formal requirementsears, formal, when-the-shalldoc-ears
test scenariosbdd, tests, scenarios, gherkindoc-bdd
architecture decisionsadr, architecture, decisiondoc-adr
system requirementssys, system, technicaldoc-sys
requirementsreq, requirement, atomicdoc-req
implementation planimpl, implementation, plandoc-impl
contractsctr, contract, api, interfacedoc-ctr
specificationsspec, specification, yamldoc-spec
taskstasks, todo, implementation tasksdoc-tasks
execution plansiplan, execution, sessiondoc-iplan
traceabilitytrace, traceability, linkstrace-check
validationvalidate, quality, compliancedoc-validator
diagramsdiagram, mermaid, chart, flowcharts-flow, mermaid-gen
roadmaproadmap, adr implementationadr-roadmap
project managementmvp, mmp, release, planningproject-mngt

Step 2: Match Skills

Match parsed intent against skill catalog:

Skill Catalog (Core Documentation Skills):

Skill IDCategoryLayerDescription
doc-brdcore-workflow1Business Requirements Documents
doc-prdcore-workflow2Product Requirements Documents
doc-earscore-workflow3EARS Formal Requirements
doc-bddcore-workflow4BDD Test Scenarios
doc-adrcore-workflow5Architecture Decision Records
doc-syscore-workflow6System Requirements
doc-reqcore-workflow7Atomic Requirements
doc-implcore-workflow8Implementation Plans (optional)
doc-ctrcore-workflow9API Contracts (optional)
doc-speccore-workflow10Technical Specifications
doc-taskscore-workflow11Implementation Tasks
doc-iplancore-workflow12Execution Plans

Quality Assurance Skills:

Skill IDCategoryDescription
trace-checkquality-assuranceValidate bidirectional traceability
doc-validatorquality-assuranceValidate documentation standards
code-reviewquality-assuranceCode quality review
contract-testerquality-assuranceTest API contracts

Utility Skills:

Skill IDCategoryDescription
charts-flowutilityMermaid architecture diagrams
mermaid-genutilityGenerate Mermaid diagrams
analytics-flowutilityAnalytics and data analysis
project-initutilityInitialize project structure

Planning Skills:

Skill IDCategoryDescription
adr-roadmapplanningADR implementation roadmaps
project-mngtplanningMVP/MMP/MMR release planning
doc-flowplanningSDD workflow orchestration

Step 3: Score and Rank

Calculate confidence scores based on:

FactorWeightDescription
Intent match40%How well request matches skill intent signals
Target match30%Explicit skill/artifact type mentioned
Context fit20%Project state and workflow position
Usage patterns10%Common skill sequences

Confidence Levels:

  • High (≥80%): Strong match, recommend with confidence
  • Medium (50-79%): Good match, include alternative options
  • Low (<50%): Weak match, suggest clarification

Step 4: Generate Recommendations

Format recommendations with rationale:

Output Format:

recommendations:
  - skill: doc-prd
    confidence: 92%
    rationale: "Request mentions 'product requirements' and 'features' - direct match for PRD creation"
    next_steps: "Run /skill doc-prd to create Product Requirements Document"

  - skill: doc-brd
    confidence: 65%
    rationale: "May need BRD first if business requirements not yet documented"
    condition: "Use if no BRD exists for this feature"

  - skill: doc-ears
    confidence: 45%
    rationale: "EARS follows PRD in workflow - consider after PRD completion"
    condition: "Use after PRD is complete"

clarification_needed: false
clarification_question: null

Example Usage

Example 1: Clear Intent

User Request: "I need to create a product requirements document for a new authentication feature"

Skill Analysis:

Intent: create (keywords: create, need)
Target: product requirements (keywords: product requirements document)
Domain: authentication feature

Recommendations:

recommendations:
  - skill: doc-prd
    confidence: 95%
    rationale: "Explicit request for Product Requirements Document"
    next_steps: "Run /skill doc-prd to create PRD for authentication feature"

  - skill: doc-brd
    confidence: 40%
    rationale: "BRD may be needed upstream if not already created"
    condition: "Check if BRD exists for authentication feature"

Example 2: Ambiguous Intent

User Request: "Help me document the system architecture"

Skill Analysis:

Intent: create (keywords: document)
Target: ambiguous - could be ADR, SYS, or diagrams

Recommendations:

recommendations:
  - skill: doc-adr
    confidence: 60%
    rationale: "Architecture decisions typically documented in ADRs"

  - skill: doc-sys
    confidence: 55%
    rationale: "System requirements capture technical architecture"

  - skill: charts-flow
    confidence: 50%
    rationale: "Architecture diagrams visualize system structure"

clarification_needed: true
clarification_question: "What aspect of architecture? (1) Decisions/rationale (ADR), (2) System specs (SYS), (3) Visual diagrams?"

Example 3: Validation Request

User Request: "Check if my documentation has proper links between artifacts"

Skill Analysis:

Intent: validate (keywords: check)
Target: traceability (keywords: links between artifacts)

Recommendations:

recommendations:
  - skill: trace-check
    confidence: 98%
    rationale: "Direct request for traceability validation"
    next_steps: "Run /skill trace-check to validate bidirectional links"

Integration with Other Skills

IntegrationDescription
context-analyzerReceives project context for better recommendations
doc-flowCan be invoked by doc-flow for skill discovery
workflow-optimizerShares workflow position awareness

Quality Gates

Definition of Done

  • User request parsed successfully
  • At least one skill recommendation provided
  • Confidence scores calculated for all recommendations
  • Rationale included for each recommendation
  • Clarification question generated when ambiguous

Performance Targets

MetricTarget
Response latency<500ms
Recommendation accuracy≥85%
User acceptance rate≥70%

Traceability

Required Tags:

@prd: PRD.000.001
@adr: ADR-000

Upstream Sources

SourceTypeReference
PRD-00Product RequirementsPRD-00
ADR-000Architecture DecisionADR-000

Downstream Artifacts

ArtifactTypeReference
Selected doc-* skillSkill ExecutionInvoked based on recommendation

Version Information

Version: 1.0.0 Created: 2025-11-29 Status: Active Author: AI Dev Flow Framework Team