AC hardcover-bookshelf
Talk to a user's Hardcover bookshelf via the Hardcover GraphQL API. Use when the user wants to manage reading activity in natural language: start a book, finish a book, view the Want to Read shelf, or compute yearly reading stats such as "how many books did I read last year?". Require HARDCOVER_TOKEN before any API call, using the exact `Bearer ...` value copied from Hardcover account API settings. Use this skill whenever the user mentions Hardcover, reading lists, bookshelves, tracking books, or anything related to managing what they're reading.
Talk to a user's Hardcover bookshelf via the Hardcover GraphQL API.
As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
How to improve
- 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: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 58/100
- 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
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 746 tokens
- 100Running it twice. No mutating operations
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- medium 6 test cases, all positive: not one "should refuse" or "should ask first"
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 552: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (1 of 2)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.