AI Company CMO Skill Discovery v1.1.0

CMO-driven skill discovery module. Multi-platform search, intelligent evaluation, and priority ranking for the AI skill learning pipeline.

Overview

ai-company-cmo-skill-discovery is the first-stage module of the AI skill learning pipeline, responsible for:

1. Multi-Platform Search: Simultaneously searching ClawHub, GitHub, NPM, PyPI, and other platforms.
2. Intelligent Evaluation: Scoring based on technical compatibility and preliminary quality assessment.
3. Priority Ranking: Composite scoring and sorting to produce a high-quality candidate list.

Core Features

Module 1: Multi-Platform Search

Function: Parallel search across multiple skill platforms.

Module 2: Intelligent Evaluation

Function: Multi-dimensional evaluation of candidate skills.

evaluation_dimensions:
  relevance:
    weight: 40%
    factors:
      - Keyword match score
      - Description relevance
      - Tag match score

  quality_preliminary:
    weight: 40%
    factors:
      - Documentation completeness
      - Community activity
      - Version update frequency
      - Test coverage (if available)

  tech_compatibility:
    weight: 20%
    factors:
      - Tech stack compatibility
      - Dependency complexity
      - Platform compatibility

Module 3: Ranking Algorithm

Function: Weighted scoring and ranking.

def calculate_score(skill):
    """Composite score: relevance 40% + quality 40% + compatibility 20%."""
    return (
        skill.relevance_score * 0.4
        + skill.quality_pre_score * 0.4
        + skill.tech_compatibility * 0.2
    )

Interface Definition

search

Execute multi-platform skill search.

Input:

query: "PDF processing"
platforms: ["clawhub", "github"]
max_results: 10
filters:
  min_quality_score: 70
  min_stars: 10
  license: "MIT"

Output:

total_found: 25
results:
  - name: "pdf-processor"
    source: "clawhub"
    url: "https://clawhub.com/skills/pdf-processor"
    description: "PDF processing skill, supports merge, split, rotate"
    relevance_score: 95
    quality_pre_score: 88
    tech_compatibility: 92
    ranking: 1
  - name: "pdf-toolkit"
    source: "github"
    url: "https://github.com/user/pdf-toolkit"
    description: "Python PDF processing tool"
    relevance_score: 85
    quality_pre_score: 75
    tech_compatibility: 80
    ranking: 2
search_metadata:
  duration_ms: 1250
  platforms_searched: ["clawhub", "github"]
  timestamp: "2026-04-15T02:50:00Z"

evaluate

Evaluate the quality of a specified skill.

Input:

skill_url: "string"
evaluation_depth: "quick|deep"

Output:

quality_score: 0-100
factors:
  documentation: 0-100
  community: 0-100
  maintenance: 0-100
  testing: 0-100
recommendation: "highly_recommended|recommended|neutral|not_recommended"

KPI Dashboard

CISO STRIDE Mitigations

CQO G2 Quality Gate

Harness Engineering — L1-L4 Layers

L4 Strategic Approval Workflow

Scope: Skills with projected impact score ≥ 8.0 (out of 10).

Rule: Development initiation requires joint approval from CEO + CMO before the CTO Agent Factory activates the build pipeline.

Workflow:

1. CMO Skill Discovery scores a skill candidate; if projected impact ≥ 8.0, the result is flagged HIGH_VALUE_CANDIDATE and routed to the approval queue.
2. CMO submits an approval request via the governance channel, including: candidate name, source URL, impact score breakdown, and proposed use case.
3. CEO reviews the strategic alignment and business case.
4. Upon dual sign-off, CTO Agent Factory is authorized to initiate development; otherwise the candidate is deferred for re-evaluation in the next quarterly cycle.

Rationale: High-impact skills consume significant Agent Factory capacity and carry cross-functional implications. Joint CEO+CMO ownership ensures strategic alignment and prevents shadow development.

Changelog

This skill is developed by AI Company CMO. A module component of ai-company-skill-learner.