BC greenhelix-agent-threat-intel-exchange
Agent Threat Intelligence Exchange. Build agent-to-agent threat intelligence marketplaces: STIX/TAXII feed listing, paywall-gated IOC access, reputation-verified intel quality, autonomous SLA negotiation, and compliance-ready audit trails. Includes detailed Python code examples for every pattern.
As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
-
low Risky intent
intent-offensive-securitySKILL.md:128Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)"description": "Command and control domain associated with APT29 campaign targeting energy sector",
detector
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 19491 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "type" - note
frontmatter-keyunknown frontmatter key "price_usd" - note
frontmatter-keyunknown frontmatter key "content_type" - note
frontmatter-keyunknown frontmatter key "executable" - note
frontmatter-keyunknown frontmatter key "install" - note
frontmatter-keyunknown frontmatter key "credentials"
Process rating: all ten parameters 50/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 10Execution cost. Instruction body is 19491 tokens: crowds the task out of the window
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 22 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- low 12 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
- +2Single-language instructions
- +3Description length 297: enough signal without eating the budget
- +4Structure: 41 headings
- +3Step-by-step instructions: 30 items
- +4Has examples (15 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.