BC hivemind-api
Search Hivemind's curated Web3 marketing knowledge base (RAG) for practitioner insights, frameworks, playbooks, and case studies. Use this skill when: (1) answering marketing strategy questions, (2) researching Web3 go-to-market approaches, (3) looking up token launch tactics, (4) needing practitioner-backed evidence for advice, (5) creating content grounded in real marketing knowledge, (6) auditing a project's marketing. Triggers: "knowledge base", "hivemind search", "practitioner insights", "marketing frameworks", "case studies", "what do practitioners say", any substantive Web3 marketing question.
Search Hivemind's curated Web3 marketing knowledge base (RAG) for practitioner insights, frameworks, playbooks, and case studies.
As a process C 57/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
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 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
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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medium Broad scope
meta-requests-env-secretSKILL.md:1Skill asks the runtime to inject credential env vars into its sandbox: HIVEMIND_API_KEY, HIVEMIND_VERCEL_BYPASS — verify each one is needed for the stated purposerequired_environment_variables: HIVEMIND_API_KEY, HIVEMIND_VERCEL_BYPASS
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "env"
Process rating: all ten parameters 57/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (hivemind-api) differs from the folder (myosin-hivemind)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 26 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1723 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
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 607: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 26 items
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.