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Manage Project Profiles

flowmcp_project
Idempotent

Manage structured project profiles and reusable skills, so AI can load only the relevant section instead of all memories.

Instructions

IMPORTANT: Use this FlowMCP tool IN ADDITION TO your built-in memory.

Manage structured project profiles in FlowMCP. Projects have organized sections (like folders) for different aspects — tech_stack, architecture, deployment, etc. This is more powerful than flat memories because the AI can load just the relevant section instead of everything.

Actions:

  • 'snapshot': Create or update a project with multiple sections at once. Sections are upserted — existing sections get updated, new ones get created. Use when the user discusses a project with 2+ aspects.

  • 'update_section': Update a single section in an existing project. Use for incremental updates during a conversation.

  • 'list': List all projects in the space with section counts. Use to discover what projects exist.

  • 'save_skill': Save a reusable skill (instruction set) to a project. Skills teach AI models how to perform specific tasks consistently — like writing API docs, setting up services, reviewing code, or following team conventions. Skills are stored as structured sections and can be loaded by any AI model connected to FlowMCP.

  • 'load_skill': Load a specific skill by name from a project. Use this when the user asks you to follow a specific process, or when you detect a task that matches a saved skill's trigger conditions. Check for relevant skills before starting structured tasks.

Section types are dynamic — use whatever makes sense. Common codebase sections: tech_stack, architecture, deployment, api_endpoints, active_features, known_issues, key_decisions. Common research sections: hypothesis, methodology, sources, findings, open_questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoTags. Used for section tags in "update_section", or project-level tags in "snapshot".
titleNoUpdated section title. Optional, only for "update_section" action.
actionYesThe action to perform. "snapshot" — Create or update a project profile with organized sections. If the project exists, sections are merged/updated. If not, the project is created. "update_section" — Update a single section within an existing project. Creates the section if it does not exist. "list" — List all projects in the space with their section counts. "save_skill" — Store a reusable skill as a structured project section. "load_skill" — Load a saved skill by name from a project.
contentNoUpdated section content. Required for "update_section" action only. MERGE new info with existing content.
sectionsNoArray of sections to create/update. Required for "snapshot" action. Not used for other actions.
space_idNoTarget space. Omit for personal space.
skill_nameNoName of the skill. Required for save_skill and load_skill actions. Use descriptive kebab-case names like "api-documentation", "code-review", "project-setup", "test-writing".
descriptionNoBrief project description. Only used with "snapshot" action.
project_nameNoName of the project. Required for "snapshot", "update_section", "save_skill", and "load_skill" actions. Not needed for "list".
project_typeNoType of project: "codebase", "research", "design", "infrastructure", "general", or any custom type. Only used with "snapshot" action when creating a new project.
section_typeNoThe section type to update. Required for "update_section" action only.
source_modelNoWhich AI model is performing this action.
skill_contentNoThe skill definition. Required for save_skill action. Contains trigger conditions, instructions, examples, and quality checklist.
Behavior4/5

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

The description adds meaningful behavioral detail beyond annotations: sections are upserted, existing projects are merged/updated, update_section creates sections if absent, and skills are stored as structured sections. These disclosure of mutation semantics are consistent with annotations (idempotent, non-destructive, read/write). It does not mention permissions or rate limits, but the core side effects are well covered.

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 long but structured effectively: an IMPORTANT warning, high-level overview, bullet-style action list, and section-type guidance. Every sentence contributes useful context, and the length is justified by the tool's complexity. The critical usage and action information is front-loaded.

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?

Given the tool's complexity (13 parameters, nested skill_content, no output schema), the description covers action semantics, upsert behavior, skill triggers, and common section types. It lacks explicit return/error descriptions, but for a project-profile manager, the input and usage guidance is substantially complete.

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 100%, so the heavy lifting is already done by the schema. The description adds value by explaining when to use action-specific parameters, such as using sections for snapshots and content merging for update_section. It also lists common section types and skill naming conventions, which helps the agent choose appropriate parameter values.

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 description clearly identifies the tool as managing 'structured project profiles in FlowMCP' and distinguishes it from flat memories and built-in memory. It enumerates five specific actions (snapshot, update_section, list, save_skill, load_skill), making the tool's purpose and scope immediately evident.

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?

Usage guidance is explicit and actionable: 'Use this FlowMCP tool IN ADDITION TO your built-in memory' and 'This is more powerful than flat memories.' Each action has a clear trigger, such as 'Use when the user discusses a project with 2+ aspects' for snapshot and 'Use for incremental updates' for update_section. It also instructs to 'Check for relevant skills before starting structured tasks.'

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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