SKILLEMALL.ai
GitHub ↗ RU Sign in

CC fill-protocol

Fill institutional Word form templates (.doc/.docx) for IRB protocols, ethics applications, grant proposals, and other structured research documents while preserving the original styles, table layouts, fonts, and page geometry. Pairs with write-protocol — write-protocol drafts the scientific content, fill-protocol renders it into the institutional template. Korean-aware (CJK eastAsia font enforcement, table cantSplit) but works for any language template.

Aperivue/medsci-skills Agent Skills author: Aperivue MIT 10 files · 6 scripts body ≈ 2 593 tokens Open the sourcegithub.com↗ analyzed 32 h ago

Fill institutional Word form templates (.doc/.docx) for IRB protocols, ethics applications, grant proposals, and other structured research documents while…

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

TemplateWordSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
77
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Concealment medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill tells the agent to hide things from you: not to show errors, not to mention actions, to report differently from what was done. You lose the ability to see what the agent really did.

For the author

Transparency beats a smooth answer. If the goal is to hide technical noise, ask the agent to "summarise briefly", not to "not mention".

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Concealment en-hide-from-user scripts/fill_form.py:77
    Instruction to hide actions from the user (quoted — discussed, not commanded)
    has silently run the author's list together. Three call sites built runs by hand and only one
    quoted

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "tools"
  • note edit-residue the text marks something as outdated (lines 35, 41, 75): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 62/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 3 mutating operations with no state check
  • 85Steps. 25 steps, 2 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2593 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 458: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.