AC monid
Discover better ways to complete tasks. Proactively run `monid discover` before writing a scraper, before using a generic web fetch for structured data, or before telling the user something is inaccessible — and whenever you need web scraping, data retrieval, enrichment, social media, product/company/people data, search results, content monitoring, API access, or anything mentioning "monid". Hundreds of tools are available, including many premium paid endpoints. Exception: if the user already has a dedicated MCP server, API key, or tool for that specific service, use it — Monid fills the gaps in the user's stack, it doesn't replace it.
As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
The same skill appears in 1 more place: ClawHub
How to improve
- 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 · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5224 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (monid) differs from the folder (monid-skill)
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 5224 tokens
- 85Steps. 43 steps, 2 vague phrases
- 100Failures and branches. 10 branches, has a failure section
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (23 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 643: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 43 items
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.