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tandem_team

Run a bounded team for development, research, analysis or review.

Instructions

Run a bounded team for development, research, analysis or review.

models reads only OMP-available openai-codex subscription models, excluding OpenRouter, ordinary OpenAI API and other providers, without a model turn. start requires a stable request_key and a complete plan with one final integration step. Independent steps run concurrently; declared file conflicts serialize. Work requires plan.allow_work; this is a live workspace, NOT an OS sandbox. The whole run owns one deadline and stops with its MCP owner, not detached. Auto selection uses Jev when configured, exporting goal/title summaries and public model facts only. Choose a model/thinking pair per step; explicit model and thinking choices win. Unassigned actionable steps are returned as pending_models, even while assigned workers run. Read selection for frozen eligible pairs, consult the OMP partner, compare once, then assign exactly every current pending step's model, thinking and reason. Never ask the user to route routine subtasks or invent model/reasoning availability. status observes the same run; never start again to wait. Worker questions use tandem_reply(task_id, question_id, answer). Cancel stops pending and active steps. Partial evidence unlocks only an explicitly opted-in read-only final synthesis. Completed reports are claims, not independent acceptance. Every response is bounded, including details. Follow readers for complete plan, selection, run errors, questions and structured results. read returns digest-bound UTF-8 byte pages; send next_request unchanged. models returns UTF-8 catalog pages from one immutable metadata observation; cursor pages never probe again. list has complete cursor continuation over run metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planNo
limitNo
actionYes
cursorNo
run_idNo
detailsNo
sectionNo
step_idNo
max_bytesNo
assignmentsNo
request_keyNo
offset_bytesNo
wait_secondsNo
expected_sha256No

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.12.0

TDQS

A4/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so thoroughly. It discloses concurrency and file-conflict serialization, the live-workspace-not-sandbox constraint, deadline ownership tied to the MCP owner, model-provider exclusions, Jev export behavior, pending_models while workers run, cancellation semantics, partial-evidence synthesis limits, and bounded paged responses.

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

Conciseness3/5

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

The description is front-loaded with purpose and contains many valuable behavioral details, but it is a dense, roughly 300-word block with compressed clauses and some awkward fragments such as 'models reads only...' and 'Read selection for frozen eligible pairs...'. It is appropriately sized for a complex orchestration tool but could be structured more cleanly.

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?

An output schema exists, so the description need not explain return values, and it does cover the run lifecycle, concurrency, model selection, cancellation, paging, and safety constraints. The remaining gaps are mainly detailed action-to-parameter mapping and explicit boundaries against overlapping sibling tools.

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 0% for the top-level parameters, so the description must compensate for 14 parameters. It adds meaning for request_key, plan completeness, allow_work, model/thinking/assignments, and cursor-based paging, but it leaves several parameters such as limit, run_id, details, section, step_id, wait_seconds, expected_sha256, offset_bytes, and project_context_id implicit or unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence states a clear verb and resource: run a bounded team for development, research, analysis, or review. The description also explains the multi-action surface, but it does not distinguish tandem_team's start/cancel/list actions from the similarly named sibling tools tandem_start, tandem_cancel, and tandem_list, leaving some overlap for an agent to resolve.

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 explicit prerequisites and alternatives for key actions: start requires a stable request_key and complete plan, work requires plan.allow_work, status is used to observe an existing run rather than starting again to wait, worker questions use tandem_reply, and cancel stops pending and active steps. It is less explicit about when to use list versus status or read, and it does not fully address sibling tools such as tandem_wait.

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