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reqs_update

Update a requirement's status, description, priority, section, test coverage, tags, or notes to keep tracked requirements current.

Instructions

Update a requirement's status, description, or metadata.

Args:

  • req_id: Requirement ID (e.g. FR-001)

  • status: New status: planned, partial, implemented, verified, superseded, obsolete

  • description: Updated description

  • priority: Updated priority: must, should, could

  • section: Updated section name

  • test_coverage: Updated test file reference

  • notes: Notes (stored in meta.notes). REPLACES the stored notes wholesale. If meta_update also carries a "notes" key, the meta_update value is the one that lands — see meta_update.

  • tags: Replace tags

  • meta_update: Merge metadata keys. notes and meta_update compose over ONE dict: notes replaces first, meta_update merges LAST. So passing both notes= and meta_update={"notes": ...} in a single call is neither an error nor a refusal — meta_update wins the collision, on every key it names. That precedence is deliberate: meta_update names the storage key directly, so it is the repair path for a key no other argument can write. Unlike the findings update tool there is no append_note here, so there is no third writer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
notesNo
req_idYes
statusNo
sectionNo
priorityNo
descriptionNo
meta_updateNo
test_coverageNo

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

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full disclosure burden and does so thoroughly: it explains that notes replace stored notes wholesale, meta_update merges last and wins collisions, and passing both is neither an error nor a refusal. It also documents that the precedence is deliberate and that no third writer exists.

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

Conciseness4/5

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

The description is longer than average, but the length is justified by the genuinely complex notes/meta_update interaction. The bulleted Args list keeps it scannable, and the core purpose is front-loaded in the first sentence.

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 nine-argument mutation tool with no annotations and no schema descriptions, the description is complete: every parameter is documented, update and replacement semantics are explicit, and the most confusing collision behavior is fully resolved. Since an output schema exists, omitting return-value details is acceptable.

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%, so the description is the only semantic source for all nine parameters. It lists every argument, enumerates valid status and priority values, and explains the replacement/merge/collision behavior for notes, tags, and meta_update. This fully compensates for the schema's lack of descriptions.

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 opening sentence names a specific operation ('Update'), a concrete resource ('a requirement'), and the targeted facets ('status, description, or metadata'). This makes the tool immediately distinguishable from sibling read/create tools like reqs_get, reqs_query, and reqs_add.

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 clear usage context for the tricky parameters: meta_update is the 'repair path for a key no other argument can write,' and it explicitly contrasts this tool with the findings `update` tool by noting there is no append_note. It does not spell out all alternatives, but the update-vs-add distinction is obvious.

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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