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sqlite-local-ai-memory

by cheveguerra
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TypeScript
Local

get_current_state

Retrieve active working dashboard, project focus, and recent milestones for high-level orientation during session bootstrap or task switching. Returns read-only markdown; use search_memory for facts.

Instructions

Retrieves the active executive working dashboard, active project focus, and recent milestones (read-only). Use during session bootstrap or task switching for high-level orientation. Do NOT use for granular fact searches (use 'search_memory'). Returns formatted markdown dashboard.

Input Schema

NameRequiredDescriptionDefault
userIdNoUser or agent namespace whose active dashboard to read. Defaults to 'user_default' when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.2
    • changedInput schema / properties / userId / description
      Previous value: -"Optional user ID to read the dashboard for."New value: +"User or agent namespace whose active dashboard to read. Defaults to 'user_default' when omitted."
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the read-only nature and the return format (formatted markdown dashboard), which covers the key behavioral traits. It does not mention auth requirements or namespace behavior beyond what the schema already states, leaving minor gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core verb and resources, then usage routing, then the return format. Three sentences with no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter read tool with no output schema, the description covers purpose, usage context, alternative, and return format. Nothing an agent needs to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is a single parameter (userId) with 100% schema description coverage that already documents its meaning and default. The description adds no additional parameter semantics, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Retrieves) plus three concrete resources (executive working dashboard, active project focus, recent milestones). It also explicitly contrasts itself with the sibling search_memory, so an agent can distinguish it without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use ('session bootstrap or task switching for high-level orientation') and when-not ('Do NOT use for granular fact searches') with the named alternative 'search_memory'. No inference is required.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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