SKILLEMALL.ai

BF forward-deployed-engineering

Guide embedded technical engagements from ambiguous stakeholder need through discovery, framing, hypothesis, build, evaluation, deployment, adoption, measurement, and generalization while preserving evidence, decision rights, and field learning. Use when one accountable technical lead must carry continuity across customer or stakeholder discovery, implementation, production fit, adoption, and measurable outcomes. Do not use for a bounded repository change, product investment governance, ongoing reliability or platform ownership, an isolated specialist task, or advisory work that ends before implementation and adoption.

magnus919/agent-skills Agent Skills author: magnus919 MIT 24 files body ≈ 2 583 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Guide embedded technical engagements from ambiguous stakeholder need through discovery, framing, hypothesis, build, evaluation, deployment, adoption…

As a process F 44/100 · Will not run — References files that are not bundled: ../neckbeard/SKILL.md, ../agent-evals-and-observability/SKILL.md, ../production-readiness/SKILL.md

AnalyzerInfrastructureOperations and projectstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: ../neckbeard/SKILL.md, ../agent-evals-and-observability/SKILL.md, ../production-readiness/SKILL.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 23. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../neckbeard/SKILL.md
  • warning missing-ref reference to a missing file: ../agent-evals-and-observability/SKILL.md
  • warning missing-ref reference to a missing file: ../production-readiness/SKILL.md
  • warning missing-ref reference to a missing file: ../product-lifecycle/SKILL.md
  • warning missing-ref reference to a missing file: ../site-reliability-engineering/SKILL.md
  • warning missing-ref reference to a missing file: ../platform-engineering/SKILL.md

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: ../neckbeard/SKILL.md, ../agent-evals-and-observability/SKILL.md, ../production-readiness/SKILL.md
  • 0Tools and files. 6 referenced file(s) missing: ../neckbeard/SKILL.md, ../agent-evals-and-observability/SKILL.md, ../production-readiness/SKILL.md
  • 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
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 8 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2583 tokens
  • 100Running it twice. Mutating operations check current state
  • 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
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 626: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 8 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: 77.