Ennodia

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds genuinely non-obvious behavioral context: cancellation cascades to child tasks, Judges, and Result Advisors, which an agent could not infer from the annotations or the single-parameter schema. It stops short of stating post-cancel run state or what happens if the run already finished.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, front-loaded with the verb and resource and immediately following with the scope of the effect. No filler.

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

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

For a single-param mutation tool with no output schema and annotations covering safety and idempotency, the description supplies the key missing piece (cascade scope). It does not describe the post-cancellation response or error behavior for an already-completed run, but nothing essential to invoking it is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter and schema description coverage is 100%, so the schema already documents runId as 'Run ID returned by ennodia_run.' The description adds nothing about the parameter, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (cancel) and resource (run) plus the cascade scope: active child task, Judge, or Result Advisor. That scope detail makes it clearly distinct from ennodia_run and ennodia_get_run, though no sibling is named explicitly, which is what would push this to a 5.

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

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

The description gives no when-to-use guidance, no prerequisites (e.g. run must be in progress), and no mention of alternatives such as ennodia_get_run for inspecting a run instead. Usage is only inferable from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already cover the read-only safety profile, and the description adds genuinely new semantics: a nonterminal response means work continues, and the agent must not treat its findings as consumed. That is real behavioral context beyond readOnlyHint. It does not cover rate limits, auth, or return shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, zero filler, and the primary action plus recommended configuration are front-loaded ahead of the caveat about nonterminal responses. Every sentence earns its place.

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

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

For a six-parameter polling tool with no output schema, the description covers the action, the recommended invocation profile, and the key interpretation pitfall. The main residual gap is that the response structure itself is undocumented anywhere, though the compact parameter description partially compensates.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each of the six parameters is already documented with defaults, ranges, and practical guidance. The description restates a recommended combination (waitMs, compact, includeEvents) but adds no syntax or format detail beyond what the schema provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb pair (inspect / wait for completion) against a named resource (a run), and the required runId parameter ties it to outputs of ennodia_run. It does not explicitly differentiate itself from ennodia_cancel_run or ennodia_history, so an agent must infer the boundary from names alone.

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

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

It gives concrete operational guidance for the polling case ('Prefer waitMs: 30000, compact: true and includeEvents: false while awaiting results') and states the condition under which the call is not finished. It stops short of naming alternatives or stating when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuine context beyond that: only *terminal* runs are persisted, the receipts live under a local history directory, and they survive a restart. It omits ordering, retention bounds, and pagination behavior, which the schema only partly supplies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler, with the scoping statement front-loaded and the usage condition following. Nothing needs trimming or reordering.

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

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

There is no output schema, so the description carries the burden of saying what comes back, and it does indicate final answers plus Judge disagreement analysis. Minor gaps remain around ordering and retention, but for a one-optional-parameter read tool it is sufficient to call correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single `limit` parameter is already well documented (newest first, max 500, exclusiveMinimum 0). The description adds nothing about the parameter, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Read terminal run receipts persisted under the local Ennodia history directory"), which is concrete and distinct from a live-run tool. It does not name any sibling such as ennodia_get_run to draw the boundary explicitly, so it falls short of full differentiation.

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

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

"Use after a restart to inspect previous final answers and Judge disagreement analysis" gives a clear triggering condition and intent. It offers no exclusions or named alternative (e.g., when to prefer ennodia_get_run for an in-flight run), which keeps it out of the top band.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare it read-only and local, so the safety profile is covered; the description adds the discovery-cache behavior (refresh re-scans), the caveat that model capabilities do not guarantee native input through a harness, and a troubleshooting-first role. It does not describe pagination or the shape of the returned list.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the action and returned facets, then layers the two directives. Dense and telegraphic but every clause carries information; no filler sentences.

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

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

No output schema exists, yet the description enumerates what discovery yields (availability, versions, capabilities, adapter notes, inputGuidance), which compensates. For a single-optional-param read tool with annotations covering safety, this is close to complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter and schema coverage is 100%, so the schema fully documents refresh. The description adds no format or semantic detail about it, which is the expected baseline when the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb (Discover) and resource (local harnesses) and enumerates the returned facets: availability, versions, capabilities, adapter notes, inputGuidance. It is clearly distinguishable from ennodia_list_skills, though it never explicitly contrasts itself with that sibling.

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

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

Gives concrete usage context: read inputGuidance before audio/image/video work, and use this first when setup or routing fails. It states when to reach for the tool but names no alternative sibling to prefer instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds a genuinely useful behavioral disclosure — that the listing deliberately omits full instruction text — which tells the agent it must follow up elsewhere to actually read a skill. It stops short of describing ordering or result shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler: it leads with the action and resource, then immediately qualifies the scope and the output limitation. Every clause earns its place.

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

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

For a zero-required-parameter, read-only listing tool with no output schema, the description plus annotations cover what an agent needs: what is listed, from where, and the key fact that instruction bodies are not included. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the single 'cwd' parameter is already documented as the way to locate project-specific skills. The description says project skills come from directories but adds no semantics beyond the schema, which is the expected baseline when the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb ('Discover') plus resource ('skills') and names the three source scopes (project, user, built-in directories), so the agent knows exactly what is returned. It does not explicitly contrast itself with the closest sibling ennodia_list_harnesses, but the resource name and the 'prompt-only' qualifier make the distinction reasonably clear.

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

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

Usage is implied: this is the discovery call you make before invoking skills. However, there is no explicit when-to-use statement, no mention of prerequisites such as needing a project context, and no routing advice versus ennodia_list_harnesses or ennodia_run.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only declare readOnlyHint=false and openWorldHint=true; the description adds the operational profile that matters here: runs "usually take minutes," they are asynchronous, and "a wait timeout does not cancel or finish the run." That is genuinely useful beyond the annotations, though it says nothing about cost, concurrency limits, or failure modes of the harness tasks.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four dense, front-loaded sentences that lead with what the tool does and end with the polling contract. Slightly redundant: "Use Plan Advisor for tailored model and skill assignments" repeats guidance already present in the pragmatic schema description.

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

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

For a 25-parameter orchestration tool with no output schema, the description covers the full lifecycle (plan -> run -> poll -> verdict), the return value (run ID), and the async/polling contract. It leaves unstated what the run-ID payload or final answer looks like, and gives no scope on run cost, which keeps it short of complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3 and the schema already covers all 25 parameters. The description still adds selection guidance the schema does not: when to set pragmatic (investigate vs patch) and how to poll via waitMs/includeEvents. It does not attempt to explain the many tuning parameters (judgeModel, nativeSandbox, isolateCwd), leaving those to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (start) and resource (Ennodia orchestration) and spells out the mechanics: plans routing, starts local harness tasks, optionally compares outputs, returns a run ID. It also distinguishes itself from the sibling ennodia_get_run by naming it as the follow-up poll step.

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

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

Explicitly positions itself as "the default entrypoint," names the alternative (ennodia_get_run) with concrete parameters (waitMs: 30000, includeEvents: false) and the condition (until terminal). It also routes agents to pragmatic mode for evidence/patch work and to Plan Advisor for model/skill assignments.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.