apollo-cost-tuning
Optimize Apollo.io costs and credit usage. Use when managing Apollo credits, reducing API costs, or optimizing subscription usage. Trigger with phrases like "apollo cost", "apollo credits", "apollo billing", "reduce apollo costs", "apollo usage".
76
72%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/saas-packs/apollo-pack/skills/apollo-cost-tuning/SKILL.mdQuality
Discovery
79%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 excels at trigger term coverage and distinctiveness, clearly carving out a niche around Apollo.io cost management with explicit trigger phrases. However, it is weak on specificity—it fails to describe any concrete actions the skill performs beyond vague 'optimize' language. Adding specific capabilities would significantly improve the description's quality.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Audits credit consumption patterns, identifies wasteful API calls, recommends plan tier changes, and tracks usage against subscription limits.'
Replace the vague 'Optimize Apollo.io costs and credit usage' opener with a list of 2-4 specific tasks the skill can accomplish.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description says 'Optimize Apollo.io costs and credit usage' but does not list any concrete actions. There are no specific capabilities described—just vague optimization language without detailing what the skill actually does (e.g., audit credit consumption, recommend plan changes, identify wasteful API calls). | 1 / 3 |
Completeness | The description answers both 'what' (optimize Apollo.io costs and credit usage) and 'when' (explicit 'Use when' clause with triggers and a 'Trigger with phrases like' section). Both are clearly stated, even though the 'what' is vague in terms of specific actions. | 3 / 3 |
Trigger Term Quality | The description explicitly lists natural trigger phrases like 'apollo cost', 'apollo credits', 'apollo billing', 'reduce apollo costs', 'apollo usage'. These are terms users would naturally say and provide good keyword coverage for this niche domain. | 3 / 3 |
Distinctiveness Conflict Risk | The skill is clearly scoped to Apollo.io cost and credit optimization, which is a very specific niche. The trigger terms all include 'apollo' making it highly unlikely to conflict with other skills. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides highly actionable, executable TypeScript code for Apollo.io cost optimization with a clear credit model reference table and concrete implementations. Its main weaknesses are the monolithic structure (all code inline rather than referenced) and the lack of explicit validation checkpoints or dry-run capabilities for credit-consuming operations. The content is mostly efficient but could be tightened by removing the Output section and trimming some code comments.
Suggestions
Add explicit validation checkpoints: a dry-run mode that reports how many credits would be consumed before actually making API calls, and a step to verify credit balance via the Apollo API before starting enrichment.
Move the implementation code into separate referenced files (e.g., credit-tracker.ts, dedup.ts, lead-scorer.ts) and keep SKILL.md as a concise overview with quick-start examples and links to the full implementations.
Remove the 'Output' section which merely restates what was already demonstrated in the code steps above it.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some unnecessary verbosity. The plan pricing section with approximate costs is useful context, but the extensive TypeScript code blocks are quite long and could be tightened. The Output section restates what was already shown. Overall mostly efficient but not maximally lean. | 2 / 3 |
Actionability | The skill provides fully executable TypeScript code with concrete implementations: a credit tracker class, LRU dedup cache, lead scoring function, budget-aware Axios client with interceptors, and a complete pipeline. All code is copy-paste ready with specific API endpoints and parameters. | 3 / 3 |
Workflow Clarity | The steps are clearly sequenced (understand model → track usage → dedup → score → budget client → pipeline), but there are no explicit validation checkpoints or feedback loops. For a cost-optimization workflow involving credit-consuming API calls (a destructive/irreversible operation), there should be verification steps like checking credit balance before starting, validating enrichment results, or dry-run modes. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections, but it's a monolithic file with ~200 lines of inline code that could be split into referenced files. The reference to 'apollo-reference-architecture' at the end is good, but the bulk of implementation code would benefit from being in separate referenced files with the SKILL.md serving as an overview. | 2 / 3 |
Total | 9 / 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
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- Reviewed
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