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 agents to work with Figma MCP in a Slides context—a companion to the base figma-use. Promises to expand design-file operations.

Checks found broken references and documentation gaps: quality_score 72 paired with process_score 43 suggests the instructions are incomplete. No critical errors, but the model wasn't run and sandbox testing didn't happen. The skill targets many platforms, yet without working examples it's hard to predict real-world behavior.

Install if you already use figma-use and need Slides support. Otherwise, test the base skill first—this one depends on it.

sst/opencode Claude Code author: sst 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
This is a copy of a skill from another catalog; the rating counts the canonical one: figma-use-slides (anomalyco/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.