deepgram-multi-env-setup
Configure Deepgram multi-environment setup for dev, staging, and production. Use when setting up environment-specific configurations, managing multiple Deepgram projects, or implementing environment isolation. Trigger: "deepgram environments", "deepgram staging", "deepgram dev prod", "multi-environment deepgram", "deepgram config management".
76
72%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/deepgram-pack/skills/deepgram-multi-env-setup/SKILL.mdQuality
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid skill description with explicit trigger terms, a clear 'Use when' clause, and a distinct niche. Its main weakness is that the capabilities described are somewhat high-level—it could benefit from listing more concrete actions like creating config files, managing API keys per environment, or setting up deployment pipelines.
Suggestions
Add more specific concrete actions such as 'create environment-specific config files, manage per-environment API keys, set up deployment pipelines' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | It names the domain (Deepgram multi-environment setup) and mentions some actions like 'setting up environment-specific configurations' and 'implementing environment isolation', but doesn't list concrete specific actions (e.g., create config files, set API keys, configure endpoints). | 2 / 3 |
Completeness | Clearly answers both 'what' (configure Deepgram multi-environment setup for dev, staging, and production) and 'when' (explicit 'Use when' clause with triggers for environment-specific configurations, managing multiple projects, or implementing environment isolation). | 3 / 3 |
Trigger Term Quality | Includes explicit trigger terms that users would naturally say: 'deepgram environments', 'deepgram staging', 'deepgram dev prod', 'multi-environment deepgram', 'deepgram config management'. These cover natural variations well. | 3 / 3 |
Distinctiveness Conflict Risk | Very specific niche combining Deepgram with multi-environment configuration. The explicit mention of 'Deepgram' plus environment-specific terms makes it highly unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
55%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides highly actionable, well-structured multi-environment setup guidance with executable code and clear validation steps. However, it is excessively verbose—much of the boilerplate (repetitive per-env configs, full Docker Compose, full K8s manifests) could be summarized or split into referenced files. The monolithic structure wastes token budget and lacks progressive disclosure.
Suggestions
Extract Docker Compose, Kubernetes overlays, and the validation script into separate bundle files (e.g., docker-compose.yml, k8s/README.md, scripts/validate.ts) and reference them from SKILL.md.
Reduce the inline config to show one environment fully and note that staging/production follow the same pattern with the differences captured in the strategy table.
Remove explanatory comments that Claude can infer (e.g., '// Convenience: transcribe with environment defaults', '// Reset for key rotation') to tighten token usage.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~200+ lines with extensive boilerplate code that Claude could generate from brief instructions. The full Docker Compose, Kubernetes overlays, and repetitive per-environment config blocks inflate token usage significantly. A concise version could convey the same strategy in a fraction of the space. | 1 / 3 |
Actionability | All code examples are fully executable TypeScript, Docker Compose YAML, Kubernetes manifests, and bash commands. The typed configuration, client factory, and validation script are copy-paste ready with concrete values and realistic patterns. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced from config definition through client factory, env vars, containerization, orchestration, and validation. Step 6 provides an explicit validation script with three test checkpoints (auth, project access, transcription) and pass/fail reporting, forming a proper feedback loop. | 3 / 3 |
Progressive Disclosure | All content is inlined in a single monolithic file with no bundle files to offload detailed code examples. The Docker Compose, Kubernetes overlays, and validation script could each be separate referenced files, but instead everything is packed into one long document with only external resource links at the bottom. | 1 / 3 |
Total | 8 / 12 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 — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
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 |
Total | 9 / 11 Passed | |
- Commit
3a2d27d
- Reviewed
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