Content
71%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.
A well-organized, appropriately progressive body that delegates deep math to a real reference file and embeds evaluation checkpoints into its guidance. Its main weakness is actionability: the compaction procedure stays at the pseudocode/conceptual level, so a reader understands the idea but cannot execute the core operation from the body alone.
Suggestions
Add a minimal executable sketch of the compaction step (e.g., the per-position scoring and masking loop in the reference's conceptual block) so the core operation is reproducible, not just described.
De-duplicate the three modifications between 'Core Concepts' and 'Three Inference-Time Modifications' — keep the brief list in Core Concepts and point to the detailed section instead of restating.
Consider dropping or trimming the dated metadata footer (Created/Last Updated/Version) since it adds time-sensitive bulk that does not guide usage.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient and mostly assumes Claude's competence, explaining the specialized technique (AM, KV compaction) without padding generic ML concepts. Minor trim opportunities exist: the three modifications appear both in 'Core Concepts' and again expanded in 'Three Inference-Time Modifications', and the dated metadata footer adds bulk. Not a 5 because of that overlap; not a 3 because the duplication is minor and most content earns its place. | 4 / 5 |
Actionability | Concrete guidance is present — the MAD threshold formula ('median + tau * MAD'), a numbered set of modifications, a decision-framework table, and a call-sequence example — but the core compaction procedure is conveyed as pseudocode ('compact KV(T2) using the task prompt for B') with the actual implementation deferred to the reference and external papers. Not a 4 because the executable core is incomplete; not a 2 because the guidance is specific and structural rather than vague hints. | 3 / 5 |
Workflow Clarity | A clear decision sequence is provided via the decision-framework table and 'Practical Guidance', with evaluation treated as an explicit checkpoint ('Co-design compaction with evaluation', 'Tune on validation data, not anecdotes', 'Measure end-to-end latency'). Not a 5 because there is no full validate→fix→retry feedback loop; not a 3 because evaluation checkpoints are present and the selection sequence is clear. The destructive/batch cap does not apply to this advisory skill. | 4 / 5 |
Progressive Disclosure | Clear overview structure (When to Activate, Core Concepts, Detailed Topics, Examples, Gotchas, Integration, References) with a well-signaled one-level-deep reference to ./references/attention-matching-formulation.md — verified to exist — each carrying a 'Read when:' navigation cue. The deep AM formulation is appropriately split into the reference rather than inlined. Not a 4 because references are clearly signaled and content is appropriately split with easy navigation. | 5 / 5 |
Total | 16 / 20 Passed |