SKILLEMALL.ai

AC release-feature-watcher

Use when the user wants to monitor a technical feature, bugfix, model/API update, changelog, release, package version, or PR and be notified only when a specific actionable condition is met.

ClawHub Hermes author: Abe Diaz (@abe238) v1.0.0 MIT-0 6 files body ≈ 3 237 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
60/100
Has gaps
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. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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 · 0

✓ No critical or high findings

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 190 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)

Process rating: all ten parameters 60/100

  • 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
  • 30Running it twice. 16 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 109 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 5 branches, has a failure section
  • 100Execution cost. Instruction body is 3237 tokens
  • low 17 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
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 190: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 109 items
  • +4Has examples (19 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This skill is a disclosed release-monitoring helper that creates user-directed watchers and does not show hidden data collection or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026