Content
82%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
An exemplary headless skill body: decision rules are specific, edge cases are enumerated, and safety defaults (keep-when-unsure, confidence floor) are built in. The main improvements are compressing the verbose JSON Schema representation and adding an explicit verify-before-reply step.
Suggestions
Replace the ~68-line JSON Schema block with a compact field spec (drop: array of {from, to, reason: bystander|personal_non_work, confidence 0-1}; redact: array of {index, text}) plus one small example input/output pair — this would cut the body roughly in half while making the contract even clearer.
Add an explicit final checkpoint to the workflow: before answering, verify the reply parses as one JSON object matching the schema, ranges use consecutive inclusive indexes from the input, and no context line appears in redact.
Include one short worked example (a few utterances with a bystander chat and an identifier) showing the expected JSON response, to anchor the confidence and range conventions.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The decision rules are dense and earn their tokens — no concept explanations, no padding, and app-specific knowledge Claude cannot infer (track semantics, context lines, confidence thresholds). The ~68-line JSON Schema block is the verbosity culprit: '$schema', 'title', and repeated 'additionalProperties' boilerplate could be replaced by a compact field spec plus one example output, trimming roughly half the body. | 4 / 5 |
Actionability | For an instruction-only skill the guidance is fully executable: exact input field semantics, enumerated drop/keep rules with worked micro-examples ('two unknown voices on the mic chatting about their weekend', 'love you, mom'), quantified confidence bands, an explicit non-redaction list, and a precise output contract including the empty-input case. A model can produce the correct output directly with no invented steps. | 5 / 5 |
Workflow Clarity | The sequence is clear (read the named file, in parts if long, decide per conversation, reply with one JSON object) with genuine safeguards for this judgment-heavy task: 'When unsure, keep. Only drop what the text clearly supports' and 'Do not drop below 0.5; keep instead'. It misses anchor 5 only because there is no explicit output-verification checkpoint (e.g. re-check the reply against the schema before answering), which matters since drops remove data from the journal. | 4 / 5 |
Progressive Disclosure | No bundle files exist and the skill is a single self-contained headless task, so inline placement is appropriate and sections (Rules, Input, task rules, Output schema) are well organized and navigable. It does not reach anchor 5 because at ~115 lines the output-schema block is the kind of self-contained contract that could live in a references file, and the body exceeds the lean single-file ideal. | 4 / 5 |
Total | 17 / 20 Passed |