SKILLEMALL.ai

AD fx-cli-shape

Choose the mechanism and the names for any user-facing control in fx, and check changes against the agreed shape. Covers subcommands, arguments, flags and options, settings keys in settings.json and .fx.json, environment variables (FX_ env vars), slash commands, JSON output, and exit codes. Use when adding, renaming, deprecating, removing, or reviewing one, for example "add a flag", "add an option", "new env var", "make this configurable", "let users turn on X", "add a slash command", "remove this command", "what should this flag be called", "deprecate this flag", "should this be a flag or a setting", or a diff that touches src/builtins/commands.zig, src/core/cli/, src/core/config/, or adds an FX_ env read. Not for parser internals or writing documentation prose.

vercel-labs/fx Agent Skills author: vercel-labs 4 files · 1 script body ≈ 4 225 tokens Open the sourcegithub.com↗ analyzed 87 min ago

Choose the mechanism and the names for any user-facing control in fx, and check changes against the agreed shape.

As a process D 39/100 · Unfinished process — References files that are not bundled: scripts/cli_shape_registry.json

IntegrationSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
D
39/100
Unfinished process
References files that are not bundled: scripts/cli_shape_registry.json
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
  • 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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/cli_shape_registry.json
  • note edit-residue the text marks something as outdated (lines 64, 103, 106): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: scripts/cli_shape_registry.json
  • 0Tools and files. 1 referenced file(s) missing: scripts/cli_shape_registry.json
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 4225 tokens
  • 100Steps. 48 steps
  • 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
  • low The response is described with custom markup (6 tags): a typed call is more reliable

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

  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 10 example trigger phrases
  • +4Description says when NOT to use the skill
  • +3Description length 773: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 48 items
  • +4Has examples (0 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.