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append_cos_lesson

Append one settleable CoS lesson for THIS operator only (self-improve construction). Use after a clear win/miss on a call: what worked, what failed, which principle. Short notes only — not transcripts. Re-injected at next voice mint (open + settled_keep). Faith content stays operator-authored — never invent doctrine.

[write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lessonYesOne short lesson (≤400 chars), e.g. "When three Grok tabs share freedom-ai, match by goal words not project name."
sourceNoOptional provenance (default voice_cos on MCP / chat on chat door).
companyIdNoFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A4.4/5.0
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 well. It discloses the lesson is 're-injected at next voice mint', that content stays 'operator-authored' and doctrine is never invented, and details the write-tier approval workflow. This goes well beyond a basic write operation and helps the agent understand consequences.

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 two paragraphs, front-loaded with the core purpose, followed by usage, constraints, behavioral effects, and approval notes. Every sentence adds value and there is no wasted wording, though it is slightly longer than strictly necessary due to the approval paragraph. Overall well-structured.

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 write tool with no output schema and no annotations, the description is remarkably complete. It provides the action, when to use it, content limits, what happens to the data, and approval requirements. All necessary context for correct invocation is present, making it self-sufficient.

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 coverage is 100% with detailed parameter descriptions, so the baseline is 3. The description adds some context about lesson brevity and usage, but does not need to repeat what the schema already documents. It slightly reinforces the 'lesson' parameter semantics by saying 'what worked, what failed, which principle', but adds no new parameter-level details.

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 states 'Append one settleable CoS lesson for THIS operator only' — a specific verb, resource, and scope, which immediately distinguishes it from siblings like append_cos_preference and list_cos_lessons. It is a concise, action-oriented purpose statement.

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 explicitly says 'Use after a clear win/miss on a call' and specifies what to include ('what worked, what failed, which principle'), along with a constraint ('Short notes only — not transcripts'). It does not name alternatives or when-not scenarios, but the context is clear enough for an agent to decide appropriately.

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.

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