AC freezer-sample-locator
Track and retrieve sample locations in -80°C freezers with hierarchical storage organization. Trigger conditions: - User needs to record sample storage positions (freezer ID, level, rack, box, grid position) - User requests to search samples by name, project, date, or location - User requires sample inventory management and export functionality Input: Sample metadata (name, project, quantity) and storage coordinates Output: Structured sample location records with search and export capabilities Success criteria: - Accurate position recording without conflicts - Fast search and retrieval (<1 second for 1000+ samples) - Data integrity maintained across operations - Export in multiple formats (JSON, CSV) Risk level: MEDIUM (Script execution with file system access) Technical difficulty: INTERMEDIATE Version: v1.0 Owner: 研发部 Last updated: 2026-02-06
As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 860 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "status" - note
frontmatter-keyunknown frontmatter key "risk_level" - note
frontmatter-keyunknown frontmatter key "skill_type" - note
frontmatter-keyunknown frontmatter key "owner" - note
frontmatter-keyunknown frontmatter key "reviewer" - note
frontmatter-keyunknown frontmatter key "last_updated"
Process rating: all ten parameters 57/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 6 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 79 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2996 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 860: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -216 emoji in the instructions: noise for the model
- +2Single-language instructions
- +4Structure: 53 headings
- +3Step-by-step instructions: 79 items
- +4Has examples (8 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.