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BD TaoStats Skill

Get a free API key from taostats.io and export it as an environment variable:

modbender/skill-library-mcp Agent Skills author: modbender MIT 7 files · 1 script body ≈ 4 115 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Get a free API key from taostats.io and export it as an environment variable:

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentData and analyticsFinancetype 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
82/100
safety, quality, tests
Safety 60%
98
Quality 40%
59
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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 Exfiltration exfil-secret-in-url SKILL.md:236
    Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)
    curl -s "https://api.taostats.io/api/dtao/stake_balance/latest/v1?coldkey=…" \
    vendor-hostquoted
  • low Exfiltration net-credential-use SKILL.md:236
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -s "https://api.taostats.io/api/dtao/stake_balance/latest/v1?coldkey=…" \
    vendor-host

Files scanned: 7. 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 42/100

  • 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
  • 40Consistency. Frontmatter name (TaoStats Skill) differs from the folder (bittensor-taostats)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 4115 tokens
  • 85Steps. 96 steps, 1 vague phrases
  • 100Running it twice. Mutating operations check current state
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (11 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)
  • +3Description length 77: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +4Structure: 68 headings
  • +3Step-by-step instructions: 96 items
  • +4Has examples (23 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.