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BC Tech Debt Tracker

Tech debt is one of the most insidious challenges in software development - it compounds over time, slowing down development velocity, increasing maintenance costs, and reducing code quality. This ...

modbender/skill-library-mcp Agent Skills author: modbender MIT 17 files body ≈ 4 624 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Tech debt is one of the most insidious challenges in software development - it compounds over time, slowing down development velocity, increasing maintenance…

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsOperations and projectsSoftware developmenttype 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
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
60
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-password-literal assets/sample_codebase/src/frontend.js:5
    Hard-coded password / key literal (may be an example)
    const API_KEY = "abc1…456"; // FIXME: Should be in environment
  • low Secrets in code secret-password-literal assets/sample_codebase/src/user_service.py:14
    Hard-coded password / key literal (may be an example) (placeholder value)
    API_KEY = "sk-1…def"  # FIXME: This should be in environment variables
    placeholder

Files scanned: 17. 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")

Process rating: all ten parameters 57/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 14 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (Tech Debt Tracker) differs from the folder (tech-debt-tracker)
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 4624 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 263 steps
  • 100Progress reporting. Reports progress
  • low 13 top-level sections: this looks like several domains in one skill

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
  • -43 reference files, but SKILL.md never points to them: the model will not open them
  • -33 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 200: enough signal without eating the budget
  • +4Structure: 49 headings
  • +3Step-by-step instructions: 263 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.