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Guide for setting up LaunchDarkly projects in your codebase. Helps you assess your stack, choose the right approach, and integrate project management that makes sense for your architecture.

56

Quality

70%

Does it follow best practices?

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High

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tessl review fix ./skills/agentcontrol/projects/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%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 content is a well-structured, actionable workflow with excellent progressive disclosure into a real, well-organized reference bundle. Its main weaknesses are moderate verbosity (a meta opener, a concept-explanation section, and duplicated reference listings) and the absence of an explicit fix-and-retry loop in the verification step.

Suggestions

Remove the meta opener paragraph ('You're using a skill that will guide you through...') and trim or fold the 'What Are Projects?' section into a one-line definition, since LaunchDarkly's project model is only marginally non-obvious.

Drop one of the two reference listings (Step 3 or the 'References' section) to cut duplicated tokens.

Add an explicit feedback loop in Step 5 — e.g. 'If verification fails (404, missing environments, invalid SDK key), fix and re-run before reporting results' — to complete the validate/fix/retry cycle.

DimensionReasoningScore

Conciseness

The body is mostly efficient (decision tables, tight bullets, concrete snippets), but includes unnecessary material: the meta opener 'You're using a skill that will guide you through...', the 'What Are Projects?' concept-explanation section, and a reference list duplicated in both Step 3 and the 'References' section. Fits anchor 3 — could be tightened — rather than anchor 4.

3 / 5

Actionability

Provides a concrete curl GET with headers, an executable Python SDK verification snippet, jq shape-handling commands, good/bad project-key examples, and a scenario-to-path decision table. Minor gaps remain — Step 4 items like 'Store API token securely' and 'Follow existing secrets management patterns' are advisory — so anchor 4 rather than fully copy-paste-ready anchor 5.

4 / 5

Workflow Clarity

A clear five-step sequence (explore, assess, choose path, implement, verify) with an explicit verification step containing runnable commands, plus error handling (409 conflict, the jq environments-shape pitfall, and an edge-case table). Not anchor 5 because there is no explicit validate-then-fix-then-retry feedback loop after a failed verification.

4 / 5

Progressive Disclosure

The body is a clear overview with well-signaled, one-level-deep references: all 9 files in references/ are real, match the links in the body, and are navigable via Step 3's grouping by stack and by use case plus a complete References section. Detailed per-language implementation is properly split into separate files — matches anchor 5.

5 / 5

Total

16

/

20

Passed

Description

53%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 identifies its LaunchDarkly niche and what the skill does, but it lacks any explicit 'when to use' trigger guidance, uses second-person voice, and leans on generic advisory verbs instead of concrete capabilities. Adding a 'Use when...' clause with natural trigger terms would address the main gaps.

Suggestions

Append an explicit trigger clause, e.g. 'Use when the user asks to create, clone, or set up a LaunchDarkly project, save SDK keys, or organize flags across services or regions.'

Rewrite in third person with concrete actions ('Creates LaunchDarkly projects, retrieves SDK keys, saves them to .env or secrets managers') instead of 'Helps you assess your stack, choose the right approach'.

Add natural synonyms and artifact terms users would actually say — 'feature flags', 'environments', 'SDK keys', 'project key' — to improve trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain ('setting up LaunchDarkly projects in your codebase') and a few actions ('assess your stack', 'choose the right approach', 'integrate project management'), but the verbs are advisory and generic rather than concrete operations, and the second-person 'Helps you assess' phrasing further reduces the score per guidelines. It falls at anchor 3, below anchor 4 which requires several specific actions.

3 / 5

Completeness

The 'what' is clear (setting up LaunchDarkly projects, assessing the stack, choosing an approach), but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps this dimension at 3 per the judging guidelines — exactly the anchor-3 case.

3 / 5

Trigger Term Quality

'LaunchDarkly projects', 'codebase', and 'integrate' are relevant domain keywords, but common natural phrases users would say ('create a LaunchDarkly project', 'SDK keys', 'feature flags', 'environments') are missing, matching anchor 3 rather than anchor 4's 'good keyword coverage'.

3 / 5

Distinctiveness Conflict Risk

'LaunchDarkly projects' is a distinct niche with a specific product name, but the body reveals closely related sibling skills (configs-create, sdk, configs-targeting) and the generic 'project management' phrasing plus absent trigger guidance leaves minor mis-trigger risk — best fit is anchor 4, not 5 which requires distinct triggers.

4 / 5

Total

13

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
launchdarkly/ai-tooling
Reviewed

Table of Contents

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