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modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 128 tokens Open the sourcegithub.com analyzed 2 d ago

Manage a local GitHub knowledge base and provide GitHub search capabilities via gh CLI.

As a process F 41/100 · Will not run — References files that are not bundled: /<name>, /project-name

ReferenceGitHubSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
F
41/100
Will not run
References files that are not bundled: /<name>, /project-name
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: /<name>
  • warning missing-ref reference to a missing file: /project-name

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: /<name>, /project-name
  • 0Tools and files. 2 referenced file(s) missing: /<name>, /project-name
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 100Steps. 29 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1128 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (10 tags): a typed call is more reliable

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)
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 387: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (9 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.