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AF peer-review-response-drafter

Assist in drafting professional peer review response letters. Trigger when user mentions "reviewer comments", "response letter", "peer review", "revise and resubmit", "R&R", "reviewer feedback", or needs help responding to academic journal reviewers.

modbender/skill-library-mcp Hermes author: modbender MIT 5 files body ≈ 1 997 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Assist in drafting professional peer review response letters.

As a process F 63/100 · Will not run — References files that are not bundled: references/examples/

AnalyzerSoftware developmentData and analyticsResearchtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
F
63/100
Will not run
References files that are not bundled: references/examples/
Tools and files w 18
0
Failures and branches w 10
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.
  2. The text references files that are not there: add them or drop the references.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 250 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning missing-ref reference to a missing file: references/examples/
  • note frontmatter-key unknown frontmatter key "status"
  • note frontmatter-key unknown frontmatter key "risk_level"
  • note frontmatter-key unknown frontmatter key "skill_type"
  • note frontmatter-key unknown frontmatter key "owner"
  • note frontmatter-key unknown frontmatter key "reviewer"
  • note frontmatter-key unknown frontmatter key "last_updated"

Process rating: all ten parameters 63/100

Will not run. References files that are not bundled: references/examples/
  • 0Tools and files. 1 referenced file(s) missing: references/examples/
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 61 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1997 tokens
  • 100Running it twice. No mutating operations
  • 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

  • +4Description does not say when NOT to use the skill (false activations)
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +5Description quotes 5 example trigger phrases
  • +3Description length 250: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 61 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.