SKILLEMALL.ai

CD figma-use-slides

This skill helps agents use Figma's use_figma MCP tool in the Slides context. Can be used alongside figma-use which has foundational context for using the use_figma tool.

The skillemall take

The skill teaches an agent to work with Figma MCP in a Slides context—supplements the foundational figma-use with presentation-specific instructions. In practice: grade C, quality 72%, process 43%. Seven files, but half have broken references or missing files. No critical bugs, lint is clean. Model never ran, sandbox untested.

For an agent, this means: instructions exist but incomplete. If you already use figma-use and specifically need slide handling, you can try it. If you lack confidence in the base skill or need a working guarantee, it's too early. Fixing broken references and running on models would have been worth it before release.

anomalyco/opencode Claude Code author: anomalyco MIT 7 files body ≈ 5 411 tokens Open the sourcegithub.com↗ analyzed 5 d ago

This skill helps agents use Figma's usefigma MCP tool in the Slides context.

As a process D 43/100 · Unfinished process — References files that are not bundled: ../figma-use/SKILL.md

ProcedureFigmaDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
43/100
Unfinished process
References files that are not bundled: ../figma-use/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

The same skill appears in 1 more place: opencode

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5411 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: ../figma-use/SKILL.md

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: ../figma-use/SKILL.md
  • 0Tools and files. 1 referenced file(s) missing: ../figma-use/SKILL.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 5411 tokens
  • 85Steps. 47 steps, 1 vague phrases
  • 100Failures and branches. 8 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 170: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 47 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.