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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
query_impactA

查询一个图节点的变更影响范围(谁会被这个节点的变更波及)。

何时必须调用:

  • 修改任何已有数据结构、模块或需求之前

  • 收到图变更通知、评估自己负责区域是否需要更新时

  • 规划跨模块任务、需要完整依赖上下文时

何时不需要:

  • 纯新增且明确无下游依赖的独立模块

参数:

  • node_id: 图节点 id(命名规范: data:user_table / module:auth_svc / req:login)

  • direction: "downstream"=谁被我影响 / "upstream"=我依赖谁

返回: [{id, layer, type, status, summary, path, hops}] 按传播距离排序。 返回的 path 是指针——细节由 skill 按指针从源头加载,不要向本工具索要内容全文。

query_contextA

图导航:查询节点的邻域导航信息,用于 Agent 诞生后构建工作上下文。

何时必须调用:

  • 接到任何涉及已有节点(数据结构/模块/需求)的任务时,第一步调用

  • 收到 Hook 任务通知、需要了解变更节点的宏观环境时

何时不需要:

  • 已经持有该节点邻域信息的连续会话中(避免重复调用)

参数:

  • node_id: 图节点 id

返回: {id, type, layer, name, summary, path, status, skill_hint, neighborhood} 返回的是导航信息而非内容本身——按 path 指针从源头(git/文档/schema)加载细节。 skill_hint 是处理建议,实际路由由 harness 的 skill_routes.yaml 决定。

submit_graph_intentA

提交图变更意图请求(开发完成后的必经步骤)。缓存为 pending,git 提交后由 review 核验。

何时必须调用:

  • 完成任何涉及图变更的开发任务后、创建 git commit 之前

  • 变更包括: 新增/修改节点(模块/数据结构/需求)、新增/删除依赖边

何时不需要:

  • 未产生任何结构变更的纯阅读/查询任务

参数:

  • intent_json: JSON 字符串,结构: {task_id, base_revision, nodes_to_create:[{id,label,props}], nodes_to_update:[{id,props}], edges_to_create:[{from,type,to,props}], edges_to_remove:[{from,type,to}], work_notes, summary, actor} work_notes 必填工作过程状态: 为什么这么改、考虑过什么备选(下一个实例靠它重建场景)

返回: {status: "pending", task_id, path} 注意: 本工具只缓存不写入——review 失败(git 提交被拒)时 pending 不会进图。

claim_taskA

认领一个 Hook 分发的任务(多 Agent 防撞车的排他锁定)。

何时必须调用:

  • 收到任务通知、评估后确认需要响应时,开发之前先认领

  • 认领成功才开工;返回 rejected 说明他人已认领,直接放弃

何时不需要:

  • 评估后确认无需变更时(不认领,让任务自然超时或被他人处理)

参数:

  • task_id: 任务 id(来自 get_pending_tasks)

  • agent_id: 你的 Agent 角色 id(稳定命名,与订阅关系关联)

返回: {status: claimed|rejected, task_id, ...}

get_pending_intentsA

查看待核验的意图请求(review agent 专用)。

何时调用:

  • 你是 Review Agent,git hook 触发你执行核验时

  • 排查「为什么图没更新」时检查是否有滞留的 pending

何时不需要:

  • 普通开发任务(你不应该消费别人的意图请求)

返回: 意图请求列表(完整 JSON)

get_pending_tasksA

拉取任务队列(被动触达的 pull 端)。harness 执行循环中每轮调用。

何时必须调用:

  • Agent 执行循环的每轮迭代开始时(检查是否有 Hook 分发给你的任务)

何时不需要:

  • 正在处理一个任务的中间(先完成当前任务)

参数:

  • status: pending(待认领)/ claimed(已认领)/ completed

返回: 任务列表 [{task_id, source_node, message, subscribers, status, ...}] 对订阅了你的任务: 先 query_impact 评估 → 需响应则 claim_task 后开工

graph_revisionA

查询当前图版本号(写意图请求时填入 base_revision,用于过期检测)。

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.4/5.0

Scored across 7 tools

Disambiguation4/5

query_impact and query_context are clearly differentiated by their focus (propagation vs. navigation), and the core command/voting tools are distinct. However, get_pending_intents and get_pending_tasks share a similar prefix and both return lists, so an agent could initially confuse them; descriptions mitigate but do not fully eliminate this.

Naming Consistency4/5

Most tools follow a snake_case verb_noun pattern (query_impact, submit_graph_intent, claim_task, get_pending_tasks, get_pending_intents). graph_revision deviates as a noun-only identifier, and there is minor verb variance (query vs. get vs. submit), but the overall pattern is readable and predictable.

Tool Count5/5

Seven tools is well within the ideal range for a specialized graph/context server. Each tool serves a distinct part of the investigate-assess-claim-submit-review workflow with no obvious redundancy or bloat.

Completeness4/5

The tool surface covers the core lifecycle: context discovery, impact analysis, task retrieval/claiming, intent submission, pending-intent review, and revision tracking. Minor gaps exist—such as no explicit intent-cancellation or node-detail tool—but query_context and query_impact fill most needs and the workflow appears functional.

Maintenance

ActivityMaintained
ResponsivenessNo issues