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deploy_functions

Destructive

Deploy a project's Function code bundle. Project-level, not per-Function — one zip holds every handler for the project, so the name is plural.

Upload the zip first with upload_file, then pass the file id here. The zip's own layout is preserved verbatim, so handler dotted paths point into it directly: a handler of 'orders.before.validate' needs orders/before.py in the zip. Dependencies must be vendored into the zip (pip install -r requirements.txt -t .) — the platform does not run pip on customer input.

Returns immediately with status 'deploying'. Poll list_deployments to see it settle to 'ready' or 'failed'. Rolling back is this same call with an earlier file id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoProject whose runner to deploy to. Optional if whoami returned a default_project_id.
code_file_idYesFile record ID from upload_file (e.g. 'FIL42').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only flag destructive/idempotent/readOnly; the description adds substantial behavior beyond them: async return with status 'deploying', settlement to 'ready'/'failed', verbatim zip layout preservation, and the fact that dependencies must be vendored because the platform will not run pip on customer input.

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?

Four dense sentences, each load-bearing: scope, prerequisite, packaging constraint, async/rollback. Front-loaded with the plural-naming rationale so the agent grasps the project-level model immediately.

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?

With no output schema, the description compensates by explaining the async lifecycle and how to observe completion, plus dependency vendoring and rollback. Nothing an agent needs to invoke this correctly is missing.

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 already 100%, so baseline is 3, but the description adds real meaning: code_file_id must originate from upload_file, and the zip's internal layout determines handler dotted paths (e.g. 'orders.before.validate' needs orders/before.py).

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?

States a specific verb+resource ('Deploy a project's Function code bundle') and immediately disambiguates scope with 'Project-level, not per-Function', which cleanly separates it from create_function/update_function siblings.

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?

Gives an explicit prerequisite ('Upload the zip first with upload_file, then pass the file id here'), names the follow-up tool (list_deployments) and the polling condition, and even covers the rollback path as 'this same call with an earlier file id'.

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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