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BC Repo Insights

AI-powered GitHub repository analysis. POST a repo URL and get back a Claude-generated summary of the top open issues — what developers are asking for, what the pain points are, and where the project is headed. Built as a Flask API, deployed and running on Albion AI.

ClawHub Agent Skills author: albionaiinc-del v1.1.0 MIT-0 6 files body ≈ 354 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 51/100 · Has gaps — weak spots: when it triggers, failures and branches, consistency

AnalyzerGitHubInfrastructureSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
C
51/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "permissions"

Process rating: all ten parameters 51/100

  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (Repo Insights) differs from the folder (repo-insights)
  • 60Tools and files. Uses tools (web, git, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 75Steps. 3 steps
  • 100Execution cost. Instruction body is 354 tokens

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +4No input/output examples
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 267: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 3 items
  • +3Output format is stated explicitly

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
The skill does what it advertises, but its hosted mode asks users to send a raw Anthropic API key to a third-party service without enough disclosure or key-handling controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026