SKILLEMALL.ai

BB bmad

Use this skill to run BMad (Breakthrough Method of Agile AI-Driven Development) as a harness-agnostic control-plane protocol that turns human intent into bounded, inspectable, resumable agent work. Compress intent into a five-field contract (Why, Capabilities, Constraints, Non-goals, Success signal); classify work as direct/bounded/initiative and route to the smallest safe path; carry decisions in durable artifacts; review as triage; route failure to the layer where ambiguity entered; and gate autonomy on observable acceptance with machine-readable status (draft/ready-for-dev/in-progress/in-review/done/blocked). Use when a change request, feature, delegated build, or multi-agent epic needs intent capture, bounded implementation, review, and resumability in any agent harness. Do not use for validating whether a problem is real (product-discovery), shaping bets before planning (product-shaping), formal spec/gate pipelines (spec-driven-development), or the issue-to-PR delivery flow (neckbeard).

magnus919/agent-skills Agent Skills author: magnus919 MIT 18 files · 2 scripts body ≈ 2 269 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Use this skill to run BMad (Breakthrough Method of Agile AI-Driven Development) as a harness-agnostic control-plane protocol that turns human intent into…

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 17. 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 65/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2269 tokens
    • low 13 top-level sections: this looks like several domains in one skill
    • low No test case covers injection arriving through data

    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
    • +3Description length 1006: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 27 items
    • +4Reference files are cited in the instructions (9 of 9)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.