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twilio-customer-memory

Store and retrieve customer context using Twilio Conversation Memory. Covers Memory Store provisioning, profile management, traits, observations, conversation summaries, and semantic Recall. Use this skill to give AI agents or human agents persistent memory of customer interactions across sessions and channels.

64

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./plugins/twilio-developer-kit/skills/twilio-customer-memory/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, well-sequenced integration guide with copy-paste-ready code for every endpoint and good guardrails via the CANNOT section. Weaknesses are duplicate Python/Node.js blocks inflating length, missing validate-retry loops for destructive/batch ops, and a monolithic single-file structure with no reference files to offload detail.

Suggestions

Consolidate the repeated Python and Node.js HTTP boilerplate (Basic Auth header construction) into one reusable snippet referenced per endpoint, to cut the duplication that inflates conciseness.

Add an explicit validate→fix→retry checkpoint for destructive and batch operations (e.g., verify a Lookup returns a profile before writing observations; confirm an observation write succeeded before relying on Recall), to lift workflow_clarity past the destructive/batch cap of 2.

Move the full API reference and the long Voice Agent Integration / Multi-Tenant ISV patterns into reference files (e.g. references/voice-agent.md, references/api-reference.md) linked one level deep from SKILL.md, so the overview stays lean and progressive_disclosure can score higher.

DimensionReasoningScore

Conciseness

Largely lean and code-forward with no concept padding, but duplicates near-identical Python and Node.js blocks for every endpoint and repeats verbose phrasing ('Conversation Orchestrator/Orchestrator'), so it could be tightened; not score 3 due to this duplication volume, not score 1 because it avoids explaining things Claude already knows.

2 / 3

Actionability

Provides fully executable, copy-paste-ready code with real endpoints, Basic Auth headers, concrete request bodies, and real response field access (e.g. store["sid"], recall.get("observations", [])), plus specific limits ('Batch up to 10', 'observationsLimit max 20, default 5').

3 / 3

Workflow Clarity

Quickstart steps are clearly sequenced with explicit ordering constraints ('Memory Store must be created before creating a Conversations Service') and CANNOT guardrails, but there are no explicit validate→fix→retry feedback loops for the destructive/batch operations (irreversible profile deletion, batch writes), which the rubric caps at 2.

2 / 3

Progressive Disclosure

Well-organized into clear sections (Overview, Prerequisites, Quickstart, Key Patterns, CANNOT, Next Steps) but monolithic — no bundle files exist and all API reference, voice-agent, and ISV content is inline rather than split into one-level-deep referenced files; not score 3 because there are no signaled external references, not score 1 because sectioning prevents a wall-of-text.

2 / 3

Total

9

/

12

Passed

Description

85%Weight 40%Scale 1-3

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 strong, third-person description that names concrete capabilities and gives an explicit 'Use this skill to...' trigger. The only weakness is moderate reliance on internal Twilio product terminology over the most common natural phrasings users would say.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Store and retrieve customer context', 'Memory Store provisioning, profile management, traits, observations, conversation summaries, and semantic Recall' — matching the score-3 anchor for multiple specific actions; not score 2 because the action list is comprehensive rather than partial.

3 / 3

Completeness

Explicitly answers both what ('Store and retrieve customer context... Covers provisioning, profiles, traits, observations, summaries, Recall') and when ('Use this skill to give AI agents or human agents persistent memory of customer interactions across sessions and channels'), with an explicit 'Use this skill to...' trigger clause.

3 / 3

Trigger Term Quality

Contains relevant natural phrases ('persistent memory', 'customer interactions', 'customer context') but leans on internal jargon ('Memory Store provisioning', 'semantic Recall', 'Conversation Memory') and misses some common user variations, so it sits at score 2 rather than the full-coverage score 3.

2 / 3

Distinctiveness Conflict Risk

Scoped specifically to Twilio Conversation Memory with distinct triggers, forming a clear niche unlikely to fire for unrelated skills; not score 2 because it is not merely 'somewhat specific' but clearly differentiated.

3 / 3

Total

11

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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