SKILLEMALL.ai

AB graphql

Designs, debugs, and hardens GraphQL schemas, resolvers, and clients: N+1 batching, nullability, cost limits, subscriptions, federation. Use when writing or reviewing a schema, SDL, or resolvers; when a query is slow or fires hundreds of database queries; when the response says "Cannot return null for non-nullable field", comes back with an errors array, or nulls a whole branch; when designing mutations, cursor pagination, custom scalars, unions, or input types; when an Apollo, Relay, or urql cache will not update after a mutation; when subscriptions drop or never fire; when adding depth, alias, complexity, or persisted-query limits, disabling introspection, or masking errors; when a schema change breaks clients; or when composing Apollo Federation subgraphs and entity references. Not for consuming someone else's GraphQL API (api) or for designing REST endpoints (rest-api).

ClawHub Agent Skills author: Iván v1.0.2 MIT-0 25 files body ≈ 5 095 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 66/100 · Nearly there — weak spots: inputs and preconditions, running it twice

IntegrationSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 25. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5095 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 66/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 9 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 5095 tokens
  • 100Steps. 49 steps
  • 100Failures and branches. 5 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +3Description length 886: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 49 items
  • +3Output format is stated explicitly
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This is a coherent GraphQL guidance skill with narrow, disclosed local preference storage and no executable payload, but users should sanitize debugging data before logging it.
LLM: benign (high) · VirusTotal: · 26 Jul 2026