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Entalpa Requirements MCP

Projects Fold Speckit Features

projects_fold_speckit_features

After projects_import_speckit: fold the imported Spec Kit features into one backlog, oldest first. Later features revise the stories they change instead of adding copies, requirements are linked to their stories, engineering-only features are left out, and possible replacements become open questions. Uses AI, spends credits, and saves each feature as it is folded; run again to resume.

Input Schema

NameRequiredDescriptionDefault
project_idYesProject UUID (database id).
max_featuresNoFold at most this many features now (1 to 300); the rest on the next call.

Output Schema

NameRequiredDescriptionDefault
featuresYes
remainingYesFeatures not folded yet.
stakeholders_createdNoStakeholders added from the actors of the folded stories.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations declare only safety hints (readOnly=false, destructive=false, openWorld=true). The description adds substantial behavioral detail beyond them: it uses AI, spends credits, incrementally saves each folded feature, and encodes the folding rules (revise vs. copy, requirement-to-story linking, exclusion of engineering-only features, replacements becoming open questions).

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 trigger condition is front-loaded and the three sentences are dense but purposeful, with no filler. Some grammatical density makes it slightly harder to scan, but every clause carries semantics.

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 an AI-driven, credit-spending, resumable batch operation, it covers prerequisite, incremental persistence, side effects, and processing rules. An output schema exists, so return values need not be explained; nothing critical for correct invocation is missing.

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 100%, so both project_id and max_features are already documented in the schema. The description does not elaborate on parameter formats or defaults, so the baseline 3 applies since the schema does the heavy lifting.

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 and resource: 'fold the imported Spec Kit features into one backlog, oldest first.' It names the prerequisite sibling (projects_import_speckit) and describes the transformation outcome, so an agent can distinguish it from import/update siblings at a glance.

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?

Gives clear sequencing context ('After projects_import_speckit') and rerun guidance ('run again to resume'), telling the agent when the tool is applicable. It does not explicitly name when-not or an alternative for folding, but the trigger condition is unambiguous.

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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