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milestone_reconcile

Repairs resolution statuses for findings and requirements created before the status hook existed. Dry run by default; apply=true commits the retroactive updates.

Instructions

One-time repair (CB-107) for stream items whose source finding or requirement resolved before the status-change hook existed (CB-26). The hook keeps new resolutions in sync; this is the retroactive fix for rows it never saw.

DRY RUN BY DEFAULT — without apply=true nothing is written, and the response still lists every candidate transition it WOULD make. This is a bulk mutation, and CLAUDE.md is explicit that a repair tool which writes by default is how it becomes an accident, so the dry-run default is load-bearing and this wrapper refuses to weaken it.

Args:

  • apply: Must be a literal JSON boolean. Defaults to false (dry run). Rejected outright for any other JSON type (a string like "false", a number, null) rather than coerced by truthiness — an MCP client sends JSON over the wire, and Python's bool("0") and bool("false") are both True, which would silently turn a client's intended dry run into a write (CB-82's class of bug). CB-151: strict typing refuses this at the pydantic boundary before the tool body runs, closing the one hole the previous union annotation + isinstance check left open (1.0/0.0 coerced to a real bool before isinstance could see it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
applyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.2.2

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses the dry-run default, that nothing is written without apply=true, that the response lists candidate transitions, that this is a bulk mutation, and the strict rejection of non-boolean values — all beyond what the schema offers.

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?

The description is front-loaded with purpose and the most critical safety behavior before moving to parameter details. It is long, but every sentence earns its place by explaining non-obvious behavior; there is no filler or repetition of schema data.

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?

For a single-parameter tool with no annotations but an output schema, the description covers the operation's niche, the dry-run safety model, write behavior, and strict parameter requirements. Nothing an agent needs to invoke it safely is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description fully compensates for the single parameter. It explains that apply must be a literal JSON boolean, defaults to false, is rejected for other JSON types rather than coerced, and even documents the historical bug class motivating the strict typing.

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 description states a specific operation ('one-time repair') and a precise resource class ('stream items whose source finding or requirement resolved before the status-change hook existed'). It clearly distinguishes this tool from the hook that handles new resolutions, though it does not name or explicitly contrast a sibling tool.

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?

It gives clear usage context: the hook keeps new resolutions in sync, while this tool is the retroactive fix for rows the hook never saw. It also explains the critical apply/dry-run semantics, but it does not formally state when not to use it or list alternative tool names.

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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