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dse-loop

Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says "DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning.

Quality

82%

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SKILL.md
Quality
Evals
Security

Quality

Content

70%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered autonomous workflow with strong sequencing, validation, and error-recovery guidance tailored to EDA domain knowledge. Its weaknesses are token weight — an inlined report template and dense recovery prose — and a monolithic structure that cites a shared-references file absent from the bundle.

Suggestions

Move the DSE_REPORT.md template (and optionally the parameter-inference table) into a reference file (e.g., references/report-template.md) and link to it, cutting roughly 60 lines from SKILL.md.

Include a minimal executable parse_result.py example (even 5 lines showing argparse + regex extraction of one metric) so the 'write a parsing script' instruction is concrete rather than prescribed.

Fix the dangling ../shared-references/external-cadence.md reference — either ship the file in the bundle or inline the one-paragraph guidance it carries — since a missing path degrades both navigation and recovery instructions.

DimensionReasoningScore

Conciseness

The EDA parameter-inference table, stopping rules, and boundary-expansion logic earn their tokens, but the ~45-line inlined DSE_REPORT.md template and the winding crash-recovery paragraph are content Claude could produce unprompted or that belongs in a reference file. Fits 'mostly efficient but could be tightened' rather than the minor-trim anchor.

3 / 5

Actionability

Concrete file paths (dse_results/dse_log.csv, DSE_STATE.json), exact CSV/JSON formats, a worked inference table, and four example invocations make the guidance mostly executable. Not 5 because the parse-result script is prescribed ("write a parameter extraction script... test it on a baseline") but never exemplified.

4 / 5

Workflow Clarity

Phases 0–4 are clearly sequenced with explicit validation checkpoints and feedback loops: test the parser on a baseline run, re-validate metric comparability after a parser reimplementation, never re-run logged configs, log failed runs, and explicit stopping conditions. This matches the top anchor including error-recovery loops.

5 / 5

Progressive Disclosure

Section structure is clear, but the skill is monolithic: the report template and parameter-inference guidance would fit separate reference files, and the twice-cited ../shared-references/external-cadence.md does not exist in this bundle, leaving a broken reference. 'Some structure but could be better organized' fits better than the good-structure anchor.

3 / 5

Total

15

/

20

Passed

Description

91%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it states the concrete loop behavior, names the domain, and provides an explicit 'Use when' clause with a rich set of natural trigger terms. The only weaknesses are a slightly generic action list and one overly broad trigger ('optimize').

DimensionReasoningScore

Specificity

"Runs a program, analyzes results, tunes parameters, and iterate until objective is met or timeout" lists several concrete actions with explicit stopping conditions, and the domain (computer architecture and EDA) is named. Not 5 because the actions are loop-generic and omit concrete artifacts (e.g., the report/log outputs).

4 / 5

Completeness

It explicitly answers both what (autonomous run→analyze→tune→iterate loop for architecture/EDA) and when ("Use when user says 'DSE', 'design space exploration', ...") with concrete trigger phrases.

5 / 5

Trigger Term Quality

"DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning" covers the acronym, the full term, and multiple natural user phrasings with synonyms, matching the comprehensive anchor.

5 / 5

Distinctiveness Conflict Risk

DSE for computer architecture/EDA is a clear niche with distinct triggers, but the standalone trigger "optimize" is broad and could fire for non-EDA optimization requests, creating minor overlap risk.

4 / 5

Total

18

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 1 suspicious

Warning

Total

13

/

16

Passed

Repository

wanshuiyin/Auto-claude-code-research-in-sleep

Path

skills/dse-loop/SKILL.md

Reviewed

Table of Contents

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