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agent-orchestration-improve-agent

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

68

1.54x
Quality

57%

Does it follow best practices?

Impact

82%

1.54x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/agent-orchestration-improve-agent/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

56%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.

The body is a well-sequenced, four-phase optimization workflow with strong validation and rollback feedback loops, but it is verbosity-padded in places and its command templates are placeholder stubs rather than executable guidance.

Suggestions

Remove the verbatim description repeat and the 'Extended thinking' prose block; fold the four 'Instructions' lines into the phase headers to eliminate duplication.

Replace placeholder command stubs ('Use: context-manager', '[X%]') with concrete, copy-pasteable commands or explicitly mark the referenced tools as prerequisites to invoke.

Split the detailed metrics catalogs (3.3) and test-suite spec (3.1) into reference files and link to them from the main workflow to improve progressive disclosure.

DimensionReasoningScore

Conciseness

Content is mostly efficient structured lists, but it repeats the description verbatim (line 8), carries a padded 'Extended thinking' prose block, and duplicates the phase structure in a separate 'Instructions' summary that could be trimmed.

3 / 5

Actionability

It gives concrete thresholds (p<0.05, Cohen's d, rollback percentages, version format) but the command blocks are stubs referencing assumed tools ('Use: context-manager') filled with $ARGUMENTS and [X%] placeholders rather than executable code.

3 / 5

Workflow Clarity

A clear four-phase sequence is paired with explicit validation (A/B testing, regression suites), feedback loops (rollback: detect→alert→switch→analyze→fix→retest), and checklists (rollback triggers, test categories).

4 / 5

Progressive Disclosure

Headers organize the single 345-line file well, but no bundle files exist and detailed metrics/test catalogs that could live in separate reference files are inlined with no external references signaled.

3 / 5

Total

13

/

20

Passed

Description

58%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.

The description clearly states what the skill does and names several concrete methods, but omits any explicit trigger ('Use when') guidance, which limits completeness and trigger-term quality. It is reasonably distinct from sibling skills.

Suggestions

Append a 'Use when...' clause with concrete trigger phrases, e.g. 'Use when improving an existing agent's performance, analyzing failure modes, or running A/B tests on prompts.'

Add natural synonyms users might say ('agent optimization', 'tune my agent', 'agent evaluation') to broaden trigger coverage.

Tighten 'continuous iteration' into a more concrete action such as 'iterative prompt tuning with regression testing'.

DimensionReasoningScore

Specificity

Names the domain (improving existing agents) and three concrete methods — 'performance analysis', 'prompt engineering', and 'continuous iteration' — which lists several specific actions with only minor coverage gaps (testing/deployment are omitted).

4 / 5

Completeness

It clearly answers 'what' but provides no explicit 'when' guidance; per the rubric a missing 'Use when' clause caps completeness at 3.

3 / 5

Trigger Term Quality

Contains relevant keywords ('improvement of existing agents', 'performance analysis', 'prompt engineering') but lacks 'Use when' phrasing and common synonyms a user would naturally say, so coverage is partial.

3 / 5

Distinctiveness Conflict Risk

It carves a clear niche (improving existing agents rather than building new ones), leaving only minor overlap risk with related agent-building or orchestration skills.

4 / 5

Total

14

/

20

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
rmyndharis/antigravity-skills
Reviewed

Table of Contents

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