Skip to main content
Glama
JoeGlenn1213

ActionD

by JoeGlenn1213
OverviewSchemaRelated ServersScoreDiscussions
Go
Local

actiond_handoff_pack

Read-onlyIdempotent

Generate a complete handoff package with git history, CI/CD results, and task details so another agent can resume work with full context. Returns structured JSON and Markdown summary.

Instructions

Generate a handoff package that lets another agent (or human) resume this work with full context, aggregating git log, ActionD CI/CD verdicts, and — when task_id is given — the task report from the connected task management system. Returns structured JSON plus a ready-to-use Markdown document covering: goal, current state (with evidence level), completed work (recent commits), pending work, known failures, decisions, verification state, and a suggested next action. The markdown field alone is designed to give the receiving agent everything it needs without reading the original session; missing information is marked unknown rather than guessed. Optional path (defaults to the current directory), task_id, project_id, from_agent/to_agent, goal, suggested_next_action, pending_work (comma-separated), and ttl_hours for the validity window (default 24).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoOne-sentence task goal
pathNoRepository path (defaults to the current directory)
task_idNoTask ID; when provided, the task report is also queried to fill in goal and decisions
to_agentNoIdentity of the agent receiving the work (e.g., 'claude')
ttl_hoursNoHow long the handoff stays valid, in hours (default 24)
from_agentNoIdentity of the agent handing off the work (e.g., 'codex')
project_idNoProject ID in the task management system (defaults to the repository name)
pending_workNoComma-separated list of pending work items
suggested_next_actionNoNext step the receiving agent should take

Schema Changelog

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

  1. Changed9 schema fields changedv0.1.1
    • changedInput schema / properties / from_agent / description
      Previous value: -"交接发起方（如 dsh:codex）"New value: +"Identity of the agent handing off the work (e.g., 'codex')"
    • changedInput schema / properties / goal / description
      Previous value: -"任务目标一句话"New value: +"One-sentence task goal"
    • changedInput schema / properties / path / description
      Previous value: -"仓库路径（默认当前目录）"New value: +"Repository path (defaults to the current directory)"
    • changedInput schema / properties / pending_work / description
      Previous value: -"待办清单（逗号分隔）"New value: +"Comma-separated list of pending work items"
    • addedInput schema / properties / project_id
      Added value: +{
+  "description": "Project ID in the task management system (defaults to the repository name)",
+  "type": "string"
+}
    • changedInput schema / properties / suggested_next_action / description
      Previous value: -"建议接手方执行的下一步"New value: +"Next step the receiving agent should take"
    • changedInput schema / properties / task_id / description
      Previous value: -"任务 id；提供后同时查询 RMS task report 补全 goal/decisions"New value: +"Task ID; when provided, the task report is also queried to fill in goal and decisions"
    • changedInput schema / properties / to_agent / description
      Previous value: -"接手方（如 dsh:claude-window）"New value: +"Identity of the agent receiving the work (e.g., 'claude')"
    • changedInput schema / properties / ttl_hours / description
      Previous value: -"交接有效期小时（默认 24）"New value: +"How long the handoff stays valid, in hours (default 24)"
  2. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare read-only, non-destructive behavior, and the description adds meaningful behavioral detail by stating it aggregates external data sources and that missing information is marked unknown rather than guessed. No contradiction with annotations exists.

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

Conciseness2/5

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

The description is verbose and redundant, repeating the purpose, output format, and parameter defaults across multiple sentences. It could be condensed into a single clear sentence plus a brief output note without losing information.

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?

Despite lacking an output schema, the description explains what the returned JSON and Markdown document contain, including the list of covered sections. It gives enough context for an agent to invoke the tool correctly, especially with all parameters optional.

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 descriptions cover all 9 parameters with 100% coverage, including defaults and conditional behavior for task_id. The tool description largely repeats the schema content and adds little new semantic meaning beyond what is already documented in the parameters.

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 generates a handoff package that aggregates git log, ActionD CI/CD verdicts, and optionally a task report, with the explicit purpose of letting another agent or human resume work with full context. It is distinct from sibling tools like actiond_status or actiond_run_report.

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 makes the primary use case explicit: use this when handing off work to another agent or human and needing consolidated context. It also provides conditional guidance ('when task_id is given') and notes defaults for path and ttl_hours, though it does not explicitly contrast with alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/JoeGlenn1213/ActionD'

If you have feedback or need assistance with the MCP directory API, please join our Discord server