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deepchat-data-import

Help developers build third-party tools that import, inspect, migrate, or analyze DeepChat data. Use when Codex needs to work with DeepChat provider configuration, model configuration, MCP/app settings, sessions, messages, legacy chat data, `agent.db`, `chat.db`, SQLCipher encrypted SQLite, Electron safeStorage wrapped passwords, Tauri importers, or native macOS/Windows/Linux data access.

80

Quality

100%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The body is a well-structured overview: lean, actionable, with a clear sequenced workflow and clean one-level-deep progressive disclosure into four real reference files. Validation checkpoints are correctly placed in the referenced database/recipe files rather than inlined.

DimensionReasoningScore

Conciseness

The ~52-line body is lean and assumes competence — it never explains what SQLite/SQLCipher/Electron is; every line (workflow steps, safety rules, source-file pointers) earns its place, matching the 'lean and efficient' anchor.

3 / 3

Actionability

As an instruction-only skill it gives concrete, specific guidance — 'Copy agent.db, agent.db-wal, and agent.db-shm', 'Prefer parameterized key APIs for SQLCipher passwords. Do not interpolate passwords into SQL', 'inspect schema_versions, sqlite_master' — with executable code and SQL deferred to the references, which the scoring notes permit.

3 / 3

Workflow Clarity

A clear five-step sequence (identify source → data-locations → sqlite-access → schema-reference → import-recipes) with safety-rule preconditions; the validation/feedback loops (validate password via sqlite_master, PRAGMA quick_check, orphaned-message checks) live in the referenced steps the workflow mandates, and the design is read-only so destructive caps do not apply.

3 / 3

Progressive Disclosure

SKILL.md is a concise overview pointing to four well-signaled, one-level-deep references (all verified to exist), with detail appropriately split into references and easy navigation; no nested reference chains.

3 / 3

Total

12

/

12

Passed

Description

100%

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 description: concrete actions, an explicit Use-when trigger rich with natural domain terms, and a clearly distinct niche. The only minor oddity is naming 'Codex' rather than the agent, but it is third-person and does not affect triggers.

DimensionReasoningScore

Specificity

Quotes four concrete verbs — 'import, inspect, migrate, or analyze DeepChat data' — naming specific actions rather than vague language, matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

It states both what ('build third-party tools that import, inspect, migrate, or analyze DeepChat data') and when via an explicit 'Use when Codex needs to work with...' trigger, satisfying the both-what-and-when anchor.

3 / 3

Trigger Term Quality

The 'Use when Codex needs to work with...' clause surfaces many natural developer terms — 'agent.db', 'chat.db', 'sessions, messages', 'provider configuration', 'SQLCipher encrypted SQLite', 'Tauri importers' — giving broad coverage of what a user would actually say.

3 / 3

Distinctiveness Conflict Risk

The DeepChat-specific niche (agent.db/chat.db, SQLCipher, Electron safeStorage, Tauri importers) is highly distinctive and unlikely to trigger for unrelated skills.

3 / 3

Total

12

/

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
ThinkInAIXYZ/deepchat
Reviewed

Table of Contents

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