BD coingecko
Live Bitcoin & crypto price data via CoinGecko API. Fetch BTC/USD, ETH/USD, multi-asset quotes. Supports both Demo (free) and Pro API keys. No credentials in prompts—only .env isolation.
Live Bitcoin & crypto price data via CoinGecko API.
As a process D 38/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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 · 5
✓ No critical or high findings
Medium and low: 5
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medium Secrets in code
secret-labelled-tokenreferences/DESCRIPTION.md:381Labelled token / key literal (vendor format unknown — verify it is not a live credential)API_KEY=CG-J…Mn3
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medium Broad scope
meta-requests-env-secretSKILL.md:1Skill asks the runtime to inject credential env vars into its sandbox: CG_API_KEY — verify each one is needed for the stated purposerequired_environment_variables: CG_API_KEY
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medium Secrets in code
secret-labelled-tokenSKILL.md:127Labelled token / key literal (vendor format unknown — verify it is not a live credential)API_KEY=CG-J…Mn3
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low Secrets in code
secret-password-literalreferences/DESCRIPTION.md:381Hard-coded password / key literal (may be an example)API_KEY=CG-J…Mn3
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low Secrets in code
secret-password-literalSKILL.md:127Hard-coded password / key literal (may be an example)API_KEY=CG-J…Mn3
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 186 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "required_environment_variables" - note
frontmatter-keyunknown frontmatter key "optional_environment_variables"
Process rating: all ten parameters 38/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Consistency. Frontmatter name (coingecko) differs from the folder (coingecko-2)
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 85Steps. 65 steps, 1 vague phrases
- 100Execution cost. Instruction body is 2566 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 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
- -215 emoji in the instructions: noise for the model
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +3Description length 186: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 65 items
- +4Has examples (7 code blocks)
- +3All 3 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.