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freedom-mcp

by com.getfreedomos

read_knowledge

Read a Markdown knowledge file by slug. Slugs are folder-qualified with NO file extension (e.g. "canon/tim-voice-guide", "content-captures/2026-07-06-forgiveness-and-the-debt") — never repo-style paths, never ".md". Returns the full content plus a list of available sections. Use this to load guidelines, SOPs, or strategies before doing work that needs to reference them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesFolder-qualified slug with no extension, e.g. "canon/tim-voice-guide" (from list_knowledge or a save_knowledge result). Never a repo-style path, never ".md".
scopeNo"company" (default) reads a company-shared file; "personal" reads from the current user's private notes.
companyIdNoFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A3.9/5.0
Behavior2/5

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

No annotations provided; description should compensate. It mentions read-only and return structure but omits error behavior (missing slug), authentication needs, or side effects. Incomplete disclosure for a tool with no annotations.

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?

Three sentences, front-loaded with action and key details. Efficient but could be slightly tighter (e.g., merging slug format and usage). No filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequately covers parameters and usage context. Missing details on output structure (what is the list of sections like?) since no output schema exists. Would benefit from describing the return format.

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 coverage 100%; description adds crucial meaning: slug format (no extension, examples), scope default, and companyId requirement. Enriches schema understanding beyond raw property 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?

Clearly states the action 'Read a Markdown knowledge file by slug' with specific examples and explains the return value (full content plus sections). Distinguishes from sibling tools like list_knowledge or save_knowledge.

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?

Explicitly says when to use: 'to load guidelines, SOPs, or strategies before doing work that needs to reference them.' Lacks explicit when-not-to-use or comparisons to alternatives like list_knowledge or read_google_doc.

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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TDQS

A3.6/5.0
Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

Resources