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Glama

TeamShared

by io.github.xhad

Context Commit

context_commit

Turn-end batch: assistant summary + durable writes + optional close.

One call replaces the end-of-turn memory_session_append + memory_remember (+ memory_session_close + memory_state_set) sequence. The append self-heals expired sessions; the response's session_id is authoritative. Returns {session_id, turn_count, reopened, memories, closed}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoWorkspace slug; scopes fact tags and the state pointer.
agentNoOverride agent identity
closeNoClose the session (queueing distillation) and clear the state pointer. Pass true when the task is done or the user says goodbye.
factsNoDurable memories to write in the same call: [{"content": "...", "kind": "fact|preference|event|note|outreach", "subject": "...", "tags": [...]}]. Only include things still true next week.
githubNoGitHub owner/repo tag for the facts.
summaryYesFaithful summary of your reply — appended as the assistant turn.
session_idNoWorking-memory session to commit to. Omit to resolve it from the conversation/active-session state pointer (requires repo).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / facts / description
      Previous value: -"Durable memories to write in the same call: [{\"content\": \"...\", \"kind\": \"fact|preference|event|note\", \"subject\": \"...\", \"tags\": [...]}]. Only include things still true next week."New value: +"Durable memories to write in the same call: [{\"content\": \"...\", \"kind\": \"fact|preference|event|note|outreach\", \"subject\": \"...\", \"tags\": [...]}]. Only include things still true next week."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool performs durable writes, can close the session, self-heals expired sessions, returns an authoritative session_id, and reports the result shape. This is solid transparency, though it stops short of covering failure modes or permission requirements.

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?

Three sentences with no filler. The core purpose is front-loaded, the replaced sequence is named, and the return shape is included. Every sentence earns its place.

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?

The definition is mostly complete for a tool with a rich schema: it names the scenario, the replaced alternatives, key behavioral nuances, and the return contract. It could be slightly more complete with explicit guidance on when not to use it, but the schema and output schema cover most operational details.

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%, so the baseline is 3. The description adds extra semantic value beyond the schema by explaining that the append self-heals expired sessions and that the response's session_id is authoritative, which directly clarifies behavior tied to the session_id parameter and the overall write semantics.

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 clearly states the tool's function: a turn-end batch that combines assistant summary, durable writes, and optional close. It also distinguishes itself from the sibling sequence by explicitly naming memory_session_append + memory_remember (+ memory_session_close + memory_state_set), so an agent can tell exactly what this tool is for.

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?

The description gives strong usage context by stating this replaces the end-of-turn memory_session_append + memory_remember sequence and that close is optional. It does not provide explicit when-not-to-use or exclusion guidance, but the naming of alternatives makes the appropriate use case clear.

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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TDQS

B3.4/5.0
Disambiguation4/5

With 104 tools across many domains (memory, work, projects, files, agents, context, strategic, ontology), the use of clear prefixes (memory_, work_, project_, file_, agent_run_, context_) makes most tools distinct. However, there are some potential confusions between memory_session_* vs memory_state_*, and memory_recall vs memory_think vs memory_assemble_context, though descriptions clarify their specific purposes. Aliases like memory_playbook_get for memory_procedure_get are explicit and reduce ambiguity.

Naming Consistency5/5

Tool names follow a highly consistent pattern: prefix_domain_action (e.g., file_create, work_update, memory_recall, agent_run_start). All use snake_case, with verbs consistently placed after the domain prefix. Even less common tools like account_brief and attention_snapshot fit the overall naming scheme, making the set predictable and easy to navigate.

Tool Count3/5

At 104 tools, this is an exceptionally large surface area, far exceeding the 25+ threshold that feels heavy. However, the server covers an extensive domain (organizational memory, work management, project tracking, file sharing, agent orchestration, and strategic planning), which justifies a large count. Still, the sheer number may overwhelm agents, and some tools could be consolidated (e.g., many memory_session_* and memory_state_* variants).

Completeness4/5

The tool surface is remarkably complete for its stated purpose, covering CRUD operations for files, work items, projects, and memory, plus lifecycle management for agents, sessions, and strategic plans. Minor gaps exist (e.g., no direct memory_item_get by ID, no section removal in projects), but agents can work around these using existing tools like memory_recall or work_create with parent_id. Overall, the set minimizes dead ends.

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