SKILLEMALL.ai

AC project-manager

Manage substantial engineering and software projects end to end: discover or bootstrap the canonical project, define scope and work breakdown, coordinate agents, maintain requirements and traceability, control changes and baselines, audit quality, and enforce release readiness. Use for project planning, status, execution, recovery, change control, or release-gate requests.

ClawHub Agent Skills author: Amine Khettat v1.4.1 MIT-0 80 files body ≈ 2 196 tokens Open the sourceclawhub.ai analyzed 5 h ago

Manage substantial engineering and software projects end to end: discover or bootstrap the canonical project, define scope and work breakdown, coordinate…

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerOperations and projectsAI and agentstype 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
56/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 80. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 148, 160): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 56/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 3 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (project-manager) differs from the folder (engineering-project-manager)
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 20 steps
    • 100Execution cost. Instruction body is 2196 tokens
    • 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

    • +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
    • -37 of 25 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 375: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (20 of 20)
    • +1License stated

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

    External checks

    ClawHub: suspicious
    This appears to be a legitimate project-management skill, but it needs review because some mutating project-file operations can be redirected by project-controlled symlinks while the skill also uses broad local Git and remote-repository authority.
    LLM: suspicious (high) · 17 Sept 2026