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resilient-data-gathering

Fallback pattern when primary tools fail - embed known data in scripts and persist to JSON for auditability

55

Quality

61%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./benchmarks/gdpval/skills/resilient-data-gathering/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The content is highly actionable with executable code and a clear sequenced workflow, but it is verbose due to duplicated examples and keeps all material inline without leveraging reference files. Tightening redundancy and splitting the full example into a reference would lift the weaker dimensions.

Suggestions

Consolidate the duplicated embedded-data Python pattern so it appears once and is referenced elsewhere, cutting significant length.

Replace the '[paste the full script from Step 3]' placeholder in Step 4 with a concrete file-based invocation to keep the workflow fully executable.

Move the full 'Complete Fallback Workflow' example into a references/ file and link to it, reducing inline bulk and improving progressive disclosure.

DimensionReasoningScore

Conciseness

The ~290-line body largely avoids explaining concepts Claude already knows but repeats the same embedded-data Python pattern across Step 3, the Best Practices snippets, and the full Example section, so it could be tightened considerably.

2 / 3

Actionability

Provides complete, executable Python (real imports, real analysis logic) and copy-paste-ready heredoc execution patterns, fully matching the 'executable, copy-paste ready' anchor.

3 / 3

Workflow Clarity

A clear 6-step sequence with a decision point and validation (Step 5 asserts JSON structure, Recovery validates artifacts), but Step 4 uses a '[paste the full script]' placeholder and the validate->fix->retry loop is soft rather than tight, leaving it just below the top anchor.

2 / 3

Progressive Disclosure

Everything is inline in one ~290-line file with no bundle files; the large duplicated code examples and full workflow example could be split into a reference file, so content that should be separate remains inline despite good section organization.

2 / 3

Total

9

/

12

Passed

Description

57%

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

The description is specific and distinctive but relies on technical jargon over natural trigger terms and lacks an explicit 'Use when...' clause. It conveys the what but only implies the when.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger phrases (e.g., 'Use when search_web, shell_agent, or execute_code_sandbox fail repeatedly with unknown errors').

Replace jargon like 'persist to JSON for auditability' with language closer to what a user would actually say when encountering repeated tool failures.

List one or two more concrete actions (e.g., 'recover intermediate results', 'audit fallback decisions') to round out the capability set.

DimensionReasoningScore

Specificity

Names concrete actions ('embed known data in scripts' and 'persist to JSON for auditability') but only offers two actions rather than a comprehensive list, matching the 'names domain and some actions' anchor.

2 / 3

Completeness

Answers 'what' clearly but the 'when' is only implied ('when primary tools fail') with no explicit 'Use when...' trigger clause, which per the guidelines caps completeness at 2.

2 / 3

Trigger Term Quality

Contains some relevant terms ('primary tools fail', 'fallback') but leans on operational jargon ('persist to JSON for auditability') rather than natural phrases a user would say, missing common variations.

2 / 3

Distinctiveness Conflict Risk

Targets a clear niche (fallback when execution tools fail) with distinct triggers, making it unlikely to fire for the wrong skill.

3 / 3

Total

9

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
HKUDS/OpenSpace
Reviewed

Table of Contents

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