fireflies-hello-world
Create a minimal working Fireflies.ai example that queries transcripts. Use when starting a new Fireflies.ai integration, testing your setup, or learning the GraphQL API patterns for meeting data. Trigger with phrases like "fireflies hello world", "fireflies example", "fireflies quick start", "simple fireflies code".
80
77%
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/fireflies-pack/skills/fireflies-hello-world/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 well-structured description with clear 'what' and 'when' clauses, explicit trigger phrases, and a highly distinctive niche. Its main weakness is that the capability description is somewhat narrow — it describes only one action (querying transcripts) rather than listing multiple concrete operations. Overall it would perform well in skill selection scenarios.
Suggestions
Consider listing additional specific actions beyond 'queries transcripts', such as 'fetches meeting participants', 'retrieves action items', or 'searches by date range' to improve specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Fireflies.ai) and a specific action (queries transcripts, creates a minimal working example), but doesn't list multiple concrete actions beyond that single capability. It mentions GraphQL API patterns but doesn't enumerate specific operations like listing meetings, extracting speakers, or filtering by date. | 2 / 3 |
Completeness | Clearly answers both 'what' (create a minimal working Fireflies.ai example that queries transcripts) and 'when' (starting a new integration, testing setup, learning GraphQL API patterns) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes explicit natural trigger phrases ('fireflies hello world', 'fireflies example', 'fireflies quick start', 'simple fireflies code') plus contextual terms like 'Fireflies.ai integration', 'GraphQL API', 'meeting data', and 'transcripts'. These cover a good range of what users would naturally say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — Fireflies.ai is a very specific product/service, and the description narrows further to 'hello world' / quick-start examples for its GraphQL API. Extremely unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 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 is a solid hello world skill with excellent actionability—all code examples are complete and executable with proper error handling. The main weakness is redundancy across three languages for the same API patterns, which inflates token cost without proportional value. Adding inline validation checkpoints and splitting language-specific examples into separate files would improve both workflow clarity and conciseness.
Suggestions
Pick one primary language for inline examples and move alternatives to separate files (e.g., HELLO_WORLD_PYTHON.md, HELLO_WORLD_BASH.md) with clear links from the main skill.
Add explicit validation checkpoints between steps, e.g., 'Verify the users array is non-empty before proceeding' after Step 1.
Remove the Output section as it merely restates what the code examples already demonstrate.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill provides four separate hello world examples (bash, TypeScript, Python) which creates redundancy—the same API patterns are demonstrated multiple times in different languages. The Output section restates what's already obvious from the code. However, it avoids explaining basic concepts and stays focused on Fireflies-specific content. | 2 / 3 |
Actionability | All code examples are fully executable and copy-paste ready with real API endpoints, proper headers, error handling, and concrete GraphQL queries. The bash curl example, TypeScript, and Python examples are all complete and runnable. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced and numbered, but there are no validation checkpoints between steps. For an API integration hello world, there should be explicit verification steps (e.g., 'Verify you see user data before proceeding to Step 2'). The error handling table is helpful but separate from the workflow itself. | 2 / 3 |
Progressive Disclosure | The skill references external resources and next steps, but the content itself is quite long with all examples inline. The multi-language examples (bash, TypeScript, Python) could be split into separate files with the SKILL.md showing just one primary example and linking to alternatives. | 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 | |
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