Thor Henning Hetland — signed knowledge web

kcp_plan

Produce a deterministic, inspectable load plan for a task against a KCP knowledge.yaml: which units to load in what order, which to skip and why, federation and budget decisions. No content is loaded and no model is called.

Input Schema

TableJSON Schema

Name	Required	Description
`env`	No	Runtime environment for federation context selection (dev/test/staging/prod)
`role`	No	Agent role for audience targeting (default: agent)
`task`	Yes	The task to plan knowledge loading for
`as_of`	No	ISO date for temporal evaluation (default: today, UTC)
`attest`	No	Attestation provider the agent can present, matched against the manifest's trusted_providers
`budget`	No	Spend ceiling for pay-per-request units
`follow`	No	Follow eligible federation refs (default false)
`strict`	No	Fail-closed: drop non-eligible units instead of listing them
`methods`	No	Payment methods the agent can settle, e.g. ["free","x402"] (default: free only)
`currency`	No	Budget currency (default USDC)
`manifest`	Yes	Path, directory, or HTTPS URL of a knowledge.yaml
`max_depth`	No	Federation hops to follow when follow=true (default 1)
`max_nodes`	No	Cap on total manifests fetched across the walk (default 64)
`max_units`	No	Cap on selected units (default 5)
`credentials`	No	Credential kinds the agent holds, e.g. ["mtls","api_key"] — opens access-gated units
`context_budget`	No	Token ceiling for what the plan loads into the caller's context window; over-budget units skipped with the arithmetic
`allow_private_hosts`	No	Permit fetches to loopback/private/link-local hosts and http:// (default false — fail-closed)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedJul 14, 2026

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses that the tool is non-destructive, deterministic, and inspectable, and lists what the plan includes (units, order, skips, federation, budget). However, it lacks details on error behavior, permissions, or rate limits, which would enhance transparency.

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 two sentences, front-loaded with the main purpose, and every word adds value. The second sentence clarifies a key limitation. No wasted text.

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?

Given the complexity (17 params, no output schema), the description outlines what the plan covers but does not describe the return format, prerequisites (e.g., accessible knowledge.yaml), or how parameters influence the plan. This leaves gaps for an agent to fully understand the tool's behavior.

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%, so baseline is 3. The description adds contextual meaning (e.g., 'federation and budget decisions' relate to follow, budget params) but does not explain parameter semantics beyond what the schema already provides. No additional value for specific parameters.

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 the tool produces a deterministic, inspectable load plan for a task against a KCP knowledge.yaml. It specifies the verb (produce), resource (load plan), and context, and distinguishes from siblings by emphasizing that no content is loaded and no model is called.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for planning before loading ('No content is loaded and no model is called') but does not explicitly state when to use this tool over alternatives like kcp_load. It provides no exclusions or prerequisites, leaving the agent to infer usage context.

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

A4.1/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: load retrieves content, plan generates a plan, replay cross-examines a plan, trace produces a decision trace, and validate lints the YAML. No overlapping functionality.

Naming Consistency5/5

All tool names follow a consistent 'kcp_verb' pattern (load, plan, replay, trace, validate), making them predictable and easy to distinguish.

Tool Count5/5

5 tools is well-scoped for the specialized domain of knowledge web planning. Each tool addresses a specific need without excess or deficiency.

Completeness4/5

The tool set covers the core workflow: planning, loading, validating, and analyzing plans. A potential minor gap is the lack of a tool to modify the knowledge configuration or list available units, but the existing surface is sufficient for its intended use.

Resources

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