SKILLEMALL.ai

AC test-fixing

Systematically identify and fix all failing tests using smart grouping strategies. Use when explicitly asks to fix tests ("fix these tests", "make tests pass"), reports test failures ("tests are failing", "test suite is broken"), or completes implementation and wants tests passing.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 756 tokens Open the sourcegithub.com analyzed 2 d ago

Systematically identify and fix all failing tests using smart grouping strategies.

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
57/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: test-fixing (sickn33/agentic-awesome-skills)

The same skill appears in 3 more places: agentic-awesome-skills, agentic-awesome-skills, RA-Skills

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: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "date_added"

    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
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 55 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 756 tokens
    • 100Running it twice. No mutating operations

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 282: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 55 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.