SKILLEMALL.ai

AB deep-coding

Deep coding multi-agent development system. Use when the user wants to build software projects using the Orchestrator to Builder to Reviewer workflow, mentions deep coding, multi-agent collaboration, orchestrator, spawn builder, spawn reviewer, or asks for complex coding projects that need module decomposition and iterative review. NOT for: simple one-liner fixes (just edit), reading code, or single-file changes.

ClawHub Agent Skills author: extraterrest v0.0.3 MIT-0 6 files body ≈ 2 096 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 73/100 · Nearly there — weak spots: result and completion, inputs and preconditions

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
73/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
40
Tools and files w 18
60
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 73/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
    • 100Steps. 45 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2096 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • 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
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 416: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 45 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    This is a coherent multi-agent coding skill, but its local dashboard has under-scoped file and log exposure risks that users should review before installing.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026