SKILLEMALL.ai

AD Project Context Guide

This skill should be used when users need to understand codebase structure, trace code decisions, analyze code dependencies and impact, identify code maintainers, or get contextual information for code reviews. It is particularly valuable for onboarding new team members, understanding legacy code, predicting code change impacts, and comprehending design decisions. The skill provides intelligent code analysis, Git history tracing, ownership tracking, and team collaboration insights to make complex codebases transparent and understandable.

ClawHub Agent Skills author: TeamoPlum v1.0.2 MIT-0 9 files body ≈ 783 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
D
41/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 41/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (Project Context Guide) differs from the folder (project-context-guide)
    • 60Tools and files. Uses tools (git) that frontmatter does not declare
    • 100Steps. 85 steps
    • 100Execution cost. Instruction body is 783 tokens
    • 100Progress reporting. Reports progress
    • 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 543: enough signal without eating the budget
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 85 items
    • +4Has examples (4 code blocks)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This skill is a local codebase analysis helper, but it also profiles contributor activity and describes broad integrations and learning behavior without clear user controls.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026