Skip to main content
Glama

Delegate a coding task (paid)

kimi_delegate

Delegate a coding task to Kimi in an isolated git worktree; get a reviewable diff to apply manually, leaving your current tree untouched.

Instructions

Delegate a coding task to Kimi (a different model) in an isolated git worktree, and get back a reviewable diff that is NOT applied to your tree.

PAID — this spends Kimi quota on every new call; use kimi_delegate_dry_run or kimi_status (both free) first if you only need to check scope or readiness.

Kimi edits files with workspace-write, but only inside a throwaway worktree seeded from your current tracked state. The returned diff is Kimi's changes; review it, then apply it yourself if you want it. Requires a git repo with at least one commit. Pass workspace_root (absolute).

NETWORK IS NOT BLOCKED: kimi has no sandbox, so a delegated task CAN reach the network — it may git push/fetch, run gh, curl, publish, or install dependencies, and it runs shell commands with your own user's privileges. Scope tasks accordingly and review the returned diff before applying it; the diff shows what changed in the worktree, not what else the run did. The Kimi model call also sends your task to your configured provider and lets Kimi read tracked files in the worktree and send their content. Kimi auto-loads the resolved workspace's AGENTS.md and discovers skills from its own config (including extra_skill_dirs, which may point outside the workspace). Skill names and descriptions are exposed to the model up front, so that content can be sent even if your prompt never mentions it. The isolation setting does not suppress any of it: kimi's built-in skills always load, and AGENTS.md is read regardless.

Your inputs are sent raw and unredacted. Secret redaction is best-effort and covers the gathered diff and Kimi's returned output — not what you type, and not the files Kimi reads for itself.

Progress & recovery: blocks up to the resolved deadline (timeout_seconds, clamped 10-600s; when omitted, the server-configured value, built-in default 300s). If that deadline expires the run is terminated and its partial output is not recoverable or resumable, so for a substantial or multi-file task that may exceed it, prefer kimi_delegate_async (a background job, built-in default 1800s deadline; poll kimi_job_status). Coarse notifications/progress streams while it blocks when your client requests it; some MCP clients background a long call before the deadline, so timeout_seconds bounds the run, not necessarily the inline wait — either way the detached run (meta.job_id) is recoverable via kimi_job_listkimi_job_statuskimi_job_result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesThe coding task for Kimi to implement inside a throwaway git worktree; the resulting diff is returned for review, not applied to your tree. Must be non-blank: empty or whitespace-only is rejected before any model call.
modelNoOverride the Kimi model slug for this call; defaults to the server/Kimi default when unset.
detailNoResponse verbosity: 'summary' (default) omits the raw model text; 'full' includes it.summary
isolationNoKimi skills isolation: which skills Kimi loads — 'inherit' (its own user/project discovery) or 'ignore-skills' (replace those with an empty directory). Kimi's built-in skills load either way. Defaults to the server's configured value (built-in 'inherit'; `kimi_status` reports the resolved one).
workspace_rootNoAbsolute path to the target repo root — pass it (or an MCP root) to target the intended repo; otherwise the call falls back to the server's own cwd and sets meta.workspace_warning.
idempotency_keyNoOptional dedup key scoped to THIS tool + workspace. Same key + same args replays the prior result with no new spend; different args are refused (idempotency_conflict). Sync and _async are separate tools and never share a key. Omit for none; retention is bounded. Lifecycle: kimi://params.
timeout_secondsNoPer-call wall-clock timeout in seconds, clamped to 10..600 (out-of-range values are coerced, not rejected). Defaults to the server's configured timeout.
reasoning_effortNoOverride the Kimi reasoning effort for this call (a model_reasoning_effort override); omit or pass null for the server default (MOONBRIDGE_REASONING_EFFORT) or Kimi's own resolution. An open, per-model string the backend validates at run time — commonly minimal|low|medium|high|xhigh; kimi_models lists each model's advertised set (advisory). Rejection and bounds detail: kimi://params.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
Behavior5/5

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

The description goes far beyond the annotations by detailing network access (no sandbox), potential git push/fetch/curl, raw input transmission, best-effort redaction, and non-resumability after timeout. This gives the agent a full risk profile and warns about side effects the annotations alone do not capture.

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?

Although long, the description earns its length: it front-loads the core purpose, uses bold for the key contract ('diff is NOT applied'), and every paragraph adds security, recovery, or alternative-tool context essential for safe use. It is structured in clear thematic blocks (purpose, cost, network, data handling, recovery).

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

Completeness5/5

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

The description covers purpose, behavior, security, error/recovery paths, timeouts, and alternatives, and an output schema exists to document return values. It is fully complete for a tool of this complexity, leaving no major gap in the agent's understanding of when and how to use it.

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 meaningful guidance by highlighting that `workspace_root` should be passed as an absolute path and by explaining the idempotency_key dedup conflict behavior. While most parameter details are in the schema, the description reinforces which parameter is critical and clarifies edge-case behavior.

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 names a specific verb ('Delegate a coding task to Kimi in an isolated git worktree') and a distinct outcome ('reviewable diff that is NOT applied'), which clearly distinguishes it from sibling tools like kimi_delegate_async and kimi_delegate_dry_run. It also states the paid nature, making the tool's purpose and value proposition unambiguous.

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?

The description explicitly tells when to use alternatives: check scope/readiness with free kimi_delegate_dry_run or kimi_status, and prefer kimi_delegate_async for substantial or multi-file tasks that may exceed the timeout. It also notes that the paid nature means the agent should consider free options first, providing clear exclusion conditions.

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/briandconnelly/moonbridge'

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