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conversation-intelligence

Twilio Conversation Intelligence development guide. Use when building real-time or post-call conversation analysis, language operator pipelines, sentiment analysis, agent assist, cross-channel analytics, or querying aggregated conversation insights (sentiment trends, escalation rates, dashboards).

61

Quality

77%

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./plugins/twilio-developer-kit/skills/twilio-conversation-intelligence/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.

An exceptionally actionable and information-dense skill — real endpoints, IDs, error codes, and executable samples throughout — weakened by cross-section redundancy and the absence of any progressive disclosure: two APIs' worth of reference material and 27 gotchas are inlined into a single 600-line file. Consolidating duplicated CANNOT/Gotcha content and moving the Insights reference into a separate file would materially improve both.

Suggestions

De-duplicate content stated in multiple sections: the JSON-only/415/20422 rule, the PUT-creates-inactive-version workaround, EXTRACTION being read-only, and pagination limits each appear in both Scope and Gotchas — state each once and cross-reference it.

Split the Conversational Insights API section (endpoints, query fields, dimensions/measures) into a references/insights.md file and keep only the 'when to use Insights vs Intelligence REST API' table inline; do the same for the 27-item Gotchas list.

Add an explicit ordered setup checklist (create Memory Store → create Orchestrator conversation config → create Intelligence config → PUT rules → verify OperatorResults flow), including a verify step after the DELETE-and-recreate configuration update workaround.

Fix the duplicate numbering in the Gotchas list (two items numbered 21) and consider replacing the 35-line ASCII pipeline diagram with a compact numbered list.

DimensionReasoningScore

Conciseness

The body is dense with non-inferable API facts, but has clear tightening opportunities: 'Cannot use PUT to update a live configuration… Workaround: DELETE the configuration and POST to recreate it' (CANNOT) restates Gotcha 4 nearly verbatim; 'JSON-only API… HTTP 415 with error 20422' appears in CANNOT, Gotcha 2, and the Insights section; pagination limits are stated in both Gotcha 27 and the Pagination section; a ~35-line ASCII diagram restates what the surrounding text already says; and the Gotchas list contains a duplicate '21.'. This is 'mostly efficient but could be tightened' (anchor 3) rather than anchor 2 — the length is factual density, not explanation of concepts Claude already knows.

3 / 5

Actionability

Fully executable, copy-paste-ready guidance: a working auth helper, complete create-configuration and PUT-rules samples against real endpoints, real operator IDs ('intelligence_operator_01kcrvw16kfa88qvgrfmr7y151'), working async pagination generators for both APIs, and exact error codes (415/20422, 70001) with the fields needed to consume results. Matches anchor 5.

5 / 5

Workflow Clarity

Sequencing is well supported — 'Low-friction entry point — start here', the Quick Decision table, the v2-vs-v3 framework, the trigger trade-off table, and a validation cue ('Implement periodic health checks to verify Memory Store linkage'). Not anchor 5: the critical end-to-end setup order (Memory Store → Orchestrator conversation config → Intelligence config → rules → verify via OperatorResults) must be assembled from Gotcha 1 plus the order of code samples rather than an explicit ordered checklist, and the destructive DELETE-and-recreate workaround has no verify step after recreation.

4 / 5

Progressive Disclosure

There are no bundle files at all — everything is inline in a ~600-line SKILL.md, including the full Insights API reference (endpoints, query fields, dimensions/measures) and 27 gotchas that clearly belong in references/ files. The two sibling-skill links are clearly signaled and one level deep, and section headers keep it navigable, which fits anchor 3 (content that should be separate is inline, but structure exists) rather than anchor 2 (minimal structure, references buried).

3 / 5

Total

15

/

20

Passed

Description

75%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.

A solid description with an explicit, concrete 'Use when…' trigger clause and good natural-keyword coverage. Its main weakness is a thin 'what' — 'development guide' names the domain without stating the concrete actions the skill performs.

Suggestions

Replace the generic 'development guide' opening with concrete action verbs, e.g. 'Configure Intelligence Configurations, Language Operators, rules, and triggers for real-time and post-call conversation analysis…' so the 'what' matches the strength of the 'when'.

Add common user synonyms to the trigger clause — 'call QA', 'post-call summaries', 'transcripts', 'conversation scoring' — to broaden natural trigger coverage.

DimensionReasoningScore

Specificity

The 'what' clause 'Twilio Conversation Intelligence development guide' is generic, but the trigger clause enumerates several concrete capabilities — 'real-time or post-call conversation analysis, language operator pipelines, sentiment analysis, agent assist, cross-channel analytics, or querying aggregated conversation insights (sentiment trends, escalation rates, dashboards)'. This matches anchor 4 (several specific actions, minor gaps such as rules/triggers/webhook configuration) rather than anchor 5, whose 'what' lists concrete action verbs like 'Extract… fill… merge'.

4 / 5

Completeness

Both parts are present: the 'what' names the domain ('Twilio Conversation Intelligence development guide') and the 'when' is explicit with concrete triggers ('Use when building real-time or post-call conversation analysis…'). It sits between anchors 4 and 5: the 'when' fully meets anchor 5, but the 'what' is a noun phrase with no concrete action verbs, so it does not clearly answer 'what does this do' at anchor-5 strength.

4 / 5

Trigger Term Quality

Natural user phrasings are well covered ('sentiment analysis', 'agent assist', 'cross-channel analytics', 'sentiment trends, escalation rates, dashboards', 'post-call'), matching anchor 4. Not anchor 5 because common variations are missing — e.g. 'call QA', 'transcripts', 'post-call summaries', 'conversation scoring' — that users of this API would plausibly say.

4 / 5

Distinctiveness Conflict Risk

The 'Twilio Conversation Intelligence' framing gives it a clear niche with distinct triggers, matching anchor 4 (mostly distinct, minor overlap). Not anchor 5 because generic terms like 'sentiment analysis' and 'conversation analysis' could pull in non-Twilio contexts, and 'querying aggregated conversation insights' overlaps the sibling conversation-orchestrator skill's territory.

4 / 5

Total

16

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (618 lines); consider splitting into references/ and linking

Warning

relative_links

Relative link issues: 2 suspicious

Warning

Total

14

/

16

Passed

Repository

openai/plugins

Path

plugins/twilio-developer-kit/skills/twilio-conversation-intelligence/SKILL.md

Reviewed

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