SKILLEMALL.ai

BD graph

Execute coding work as a cached dependency graph with local quality gates, parallel agents, localized retries, resume support, token telemetry, and an interactive report. Use for /graph requests.

ClawHub Agent Skills author: Govind Waghmare v1.0.0 MIT-0 3 files body ≈ 560 tokens Open the sourceclawhub.ai analyzed 2 d ago

Execute coding work as a cached dependency graph with local quality gates, parallel agents, localized retries, resume support, token telemetry, and an…

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
44/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 44/100

    • 0Result and completion. Does not say what the result is
    • 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. 4 mutating operations with no state check
    • 40Consistency. Frontmatter name (graph) differs from the folder (graph-skill)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
    • 100Steps. 10 steps
    • 100Execution cost. Instruction body is 560 tokens
    • low The response is described with custom markup (9 tags): a typed call is more reliable

    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)
    • +4Structure: 1 headings, hard to scan
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 195: enough signal without eating the budget
    • +3Step-by-step instructions: 10 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

    External checks

    ClawHub: clean
    This is a disclosed local coding-workflow skill with bounded agent use, local reports/cache, and no evidence of hidden or purpose-mismatched behavior.
    LLM: benign (high) · VirusTotal: · 27 Jul 2026