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memory_context_pack

Bounded resume pack for an agent starting or resuming work.

One call returns {cursor, profile_excerpt, work_open, changes, has_more_changes, recall, truncated, token_est, budget_tokens} packed to budget_tokens in that fixed section order, led by a verbatim constraints list (same as the constraints prompt) when the org has standing rules. Built from the same paths as memory_profile_get, memory_changes_since and memory_recall (shared brain: no agent filter). Persist cursor and pass it next time to receive only newer changes. Use memory_recall for further search and memory_assemble_context for a task-driven pack.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoWorkspace slug. Filters the changes section to this repo and boosts (does not filter) recall hits.
queryNoOptional short keyword anchor. When set, adds a capped, org-shared memory_recall section. Omit to skip recall.
cursorNoOpaque resume cursor from a previous memory_context_pack, memory_changes_since, or a closing context_commit / memory_session_close (handoff_cursor). Pass it back as-is. Omit on first contact to get the newest durable changes plus a cursor to resume from.
githubNoGitHub owner/repo. Filters changes to github:<owner>/<repo> and boosts recall hits.
work_idNoWork item id to include as work_open (compact row)
budget_tokensNoApprox token cap for the whole pack (default 3000)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations the description carries the full burden, and it delivers meaningful traits: fixed section order, a verbatim constraints lead when standing rules exist, 'shared brain: no agent filter', and cursor-based incremental resume. It stops short of an explicit safety/read-only statement, but the behavior disclosed is substantial.

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

Conciseness4/5

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

Front-loaded with the purpose and scoping, then progressively more detail; each sentence (return shape, build source, cursor, alternatives) earns its place. Slightly dense but well-ordered rather than padded.

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

Completeness4/5

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

Covers return shape, cursor semantics, budget behavior, and sibling alternatives; since an output schema exists the field enumeration is somewhat redundant, but nothing an agent needs to call 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?

Schema description coverage is 100%, so every parameter is already documented in the schema, and the description largely reinforces rather than extends that. It adds a little on cursor chaining and the budget cap, but not enough to move above the high-coverage baseline of 3.

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 and resource ('bounded resume pack for an agent starting or resuming work') and enumerates exactly what the single call returns. It distinguishes itself from siblings by naming memory_recall (further search) and memory_assemble_context (task-driven pack), so an agent can route without opening schemas.

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?

Explicit when-to-use ('starting or resuming work'), explicit alternative routing ('use memory_recall for further search', 'memory_assemble_context for a task-driven pack'), and explicit cursor lifecycle ('persist cursor and pass it next time to receive only newer changes').

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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