SKILLEMALL.ai
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AB submission

This skill should be used when the user asks to "write a query letter", "query", "querying", "pitch", "blurb", "back cover copy", "jacket copy", "comp titles", "comparable titles", "synopsis for agents", "submit to agents", "submission tracker", "self-publishing description", "retailer description", "ready to query", "submission readiness check", or wants to prepare and track a finished manuscript's submission to agents, publishers, or retailers.

danjdewhurst/story-skills Agent Skills author: danjdewhurst MIT 6 files body ≈ 2 931 tokens Open the sourcegithub.com↗ analyzed 2 d ago

This skill should be used when the user asks to "write a query letter", "query", "querying", "pitch", "blurb", "back cover copy", "jacket copy", "comp…

As a process B 73/100 · Nearly there — weak spots: result and completion, running it twice

GeneratorAI 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
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
B
73/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 73/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 17 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 37 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2931 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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

    • +3Output format is not stated: the model decides each time
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 13 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 450: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 37 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.