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get_project_context

Load top project and global memories to provide full context from previous sessions. Optionally pass a current task to retrieve the most relevant memories.

Instructions

Load top memories for the current project plus relevant global memories. Use at the start of a session to get full context from previous sessions. Optionally pass context to get memories most relevant to your current task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoProject identifier (auto-detected from git remote if omitted)
include_globalNoInclude global developer preferences
contextNoOptional context to improve relevance ranking (e.g., current task or topic)
context_typeNoOptional context type that shifts scoring weights. debugging = boost bug/pattern memories, planning = boost architecture/decision, reviewing = boost pattern/preference.
compactNoWhen true (default), returns only formatted_context text instead of full JSON arrays. Saves ~60% tokens.
limitNoMax total memories to return (default 25). Lower values save context tokens.
team_idNoOptional override. Team memories are automatically included for team/enterprise users.
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions the tool loads data (likely read-only) and uses auto-detection for project_id, but fails to address important aspects like permissions, rate limits, side effects, or data returned (e.g., formatted_context format). This leaves significant gaps for an agent to safely invoke the tool.

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?

Two sentences: first packs purpose and resource, second adds usage guidance and optional context. Every word earns its place. No fluff, front-loaded with critical action.

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

Completeness3/5

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

Given 7 parameters, no output schema, and many siblings, the description covers core purpose and primary usage but omits output details (e.g., compact returns formatted_context). It is adequate for a straightforward retrieval tool but could better explain return format or behavior for new users.

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

Parameters4/5

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

Schema coverage is 100%, providing baseline 3. The description adds meaningful context beyond schema: auto-detection of project_id from git remote, token savings for compact (~60%), and relevance boosting via context_type. These enrich the schema descriptions without redundancy.

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?

The description uses specific verb 'Load' and clearly identifies the resource: 'top memories for the current project plus relevant global memories'. It also suggests usage at session start and optional context passing, distinguishing it from siblings like 'list_memories' or 'recall_memories' by focusing on combined project+global retrieval with relevance ranking.

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

Usage Guidelines4/5

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

Explicitly states when to use: 'at the start of a session to get full context from previous sessions'. Also mentions optional context for task relevance. However, it does not provide explicit when-not-to-use or alternative tools, though the strong recommendation implies appropriate scenarios.

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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