OPSIN

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

With no annotations, the description carries the full burden and does well: it states the answers derive from OPSIN-signed verdicts across all notebooks, never from a model, which tells the agent the results are authoritative and non-generative. It also discloses empty-result behavior (it says so and points to opsin_propose). What it omits is the response shape and whether the call is strictly read-only, but the key trust characteristic is explicit.

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, front-loaded with the verb and the question examples, then the provenance and fallback behavior. Dense but no filler; the phrase 'Ask the signed record whether a part of an agent works' is slightly convoluted but each clause adds information.

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?

The tool is simple (one parameter, no nested objects), and the description covers purpose, data provenance, and the no-match path. However, with no output schema and no annotations, it never hints at what an answer looks like (a verdict record? prose? list?), leaving the agent guessing about return values.

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 coverage is 0% and the single 'q' parameter has no description, so the description must compensate. The quoted example queries partly do this by showing the expected granularity and phrasing of a question, but the description never states that the input is one free-text question capped at 200 characters, leaving format constraints undocumented.

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?

Specific verb (ask) plus a concrete resource (the signed record / signed verdicts) and a clear subject: whether a part of an agent works. The quoted examples ('calculator', 'answer only', 'persona', 'step by step') make the domain tangible. It does not clearly differentiate itself from sibling opsin_verdict, and 'signed record' is domain jargon an agent must infer.

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?

'before you ship it' implies a pre-deployment check context, and the description states a fallback path (offers opsin_propose when nothing matches). However, there is no explicit when-not guidance and no contrast with the many sibling query tools such as opsin_verdict or opsin_read_prompt.

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?

With no annotations, the description carries the full burden, and it does disclose one meaningful trait beyond the schema: this is an aggregate read returning preregistration, beacon, all arms with progress, prediction, and verdict. However, it does not state that it is read-only, how large the response is, or whether it is more expensive than the narrower siblings.

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 compact sentence with the scope ("in full") front-loaded and no wasted words. The fragment form and undefined nouns cost it a point but the density is appropriate.

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?

With no output schema, the description usefully enumerates the returned components, which is the main thing an agent needs to know about the payload. It still leaves the sole parameter unexplained, which is a real gap for a tool whose only input is that id.

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?

The single required parameter "id" has 0% schema description coverage and the description never mentions it, so it is unclear whether the id identifies a cycle, a market, or a suite. The description's field list implies a cycle identifier but adds no explicit meaning.

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?

"One cycle in full" combined with the enumerated contents signals a fetch of a single composite cycle record, but the verb is only implied (a fragment, not a sentence). The word "cycle" is undefined domain jargon, and nothing distinguishes this from siblings like opsin_verdict or opsin_status, which likely return overlapping data.

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?

There is no statement of when to call this instead of opsin_verdict, opsin_status, or opsin_markets, despite the description explicitly mentioning OPSIN's prediction and the verdict — the exact concepts those siblings appear to cover. The agent must guess at routing.

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?

With no annotations, the description carries the full burden, and it does disclose that execution is instant, requires no signing, and operates only on already-played-out launches. However it says nothing about the shape of the result or how the rule's performance is reported against the baseline, which is a meaningful gap for a 12-parameter backtest with no output schema.

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, front-loaded with the core action and ending with the routing instruction. The clause 'Instant and never signed' is dense but earns its place; the 'coin flip' metaphor is the only mildly ambiguous construction.

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?

Given 12 parameters, no annotations, and no output schema, the definition is reasonably complete on the input side and on when to call it. What is missing is any indication of what a preview result contains or how the rule-versus-baseline comparison is presented, which an agent needs to interpret the response.

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 every parameter is already documented in the schema, establishing a baseline of 3. The description adds no parameter-level detail beyond noting that entry timing is part of the rule, leaving the schema to do all 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 states a concrete action -- running a trading rule against the latest completed Elysium launches and benchmarking it against a random-entry ('coin flip') baseline -- which identifies both verb and resource. The scope is clear enough to distinguish it from the live-measurement sibling, though the 'coin flip' phrasing is metaphorical rather than a named object.

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 explicitly names the alternative, opsin_market_propose, and gives the condition that selects it: use this tool to fit a rule to past launches, use propose to measure it on launches that do not yet exist. The when-to-use boundary is stated without requiring inference.

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?

With no annotations, the description carries the full behavior burden. It usefully discloses the commit-measure-sign lifecycle and a hard rate limit of three per agent per day, which no structured field provides. It omits whether a hashed rule is immutable, what happens if measurement never completes, and what the call returns, which are material gaps for a commitment-style write.

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; the verb and commitment model come first and the rate limit closes it. The three-stage clause is dense enough that it takes a second read, which keeps it just short of a 5.

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 14-parameter, no-output-schema, no-annotation write tool, the description explains the concept and the cadence but not the mechanics that matter to an agent: what the returned hash is used for, whether the rule can later be amended, and how scoring against the coin flip is decided. It is adequate to identify the tool, not to call it confidently.

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 all 14 parameters carry their own descriptions (time windows, stop loss, take profit, size, launchpad enum list), so the schema already does the semantic work. The description adds no parameter-level meaning beyond calling the payload a 'trading rule', which is the baseline-3 case.

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 names the verb ('Preregister') and the resource ('a trading rule') and sketches its lifecycle (hashed, measured, signed). It never names a sibling such as opsin_market_preview or opsin_market_propose alternatives, so the agent must infer the boundary between previewing and committing.

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 lifecycle wording implies this is the commit step ahead of 'the next Elysium launches', and the rate limit ('Three a day per agent') hints at scarcity. There is no explicit statement of when to choose this over opsin_market_preview or opsin_propose, and no preconditions are spelled out.

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?

With no annotations, the description carries the full burden, and it does disclose real behavioral traits: results are ordered newest first, records are preregistered before trading and signed after, and the payload bundles a second dataset of the last day's Elysium launches with their first-hour performance. It omits anything about volume, pagination, response shape, or how the coin-flip baseline is represented, which leaves meaningful gaps for a no-annotation tool.

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?

Everything is crammed into a single run-on sentence with two unrelated payloads stacked by "and," plus nested appositives ("Elysium, the first market the lab reads,"). It is not front-loaded and reads as jargon-dense prose rather than a definition, though most of the individual facts are substantive.

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?

With no annotations, no output schema, and no parameters, the description is the only documentation, and it covers content and ordering but not the shape or interpretation of what comes back. Terms like "coin flip," "lab," and "Elysium" are used without grounding, so an agent knows roughly what the tool is about but not what it will receive.

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?

The tool takes zero input parameters, so there is no parameter semantics to explain and the baseline of 4 applies. Nothing in the description is needed to clarify call arguments.

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 names a specific resource — market trials where trading rules were switched on/off against a coin-flip control, preregistered and signed — which is more than a restatement of the name. But it never supplies an explicit verb ("List"/"Returns"), so the agent must infer this is a read/list endpoint, and it draws no boundary against siblings such as opsin_market_preview or opsin_suites.

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?

There is no statement of when to call this versus any of the twelve sibling tools, nor any preconditions or exclusions. The closest thing to guidance is implicit: it returns historical trial results plus recent launches, which an agent could guess is for post-hoc analysis, but nothing in the text says so.

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?

With no annotations at all, the description carries the full burden, and it does disclose genuinely useful traits: no cost, no latency, and no signature/commitment side effect, implying a non-mutating simulation. It does not say whether anything is persisted, what the response contains, or that results are in-sample fits over history, which the phrase "a rule can be fitted to history" only vaguely gestures at.

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 short sentences with no padding, which is appropriately sized. However, the wording is aphoristic rather than front-loaded with a clear action and object, so the reader must decode slogans ("against a coin flip," "fitted to history") before understanding the tool.

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?

A 12-parameter simulation tool with no annotations and no output schema needs the description to explain both behavior and what comes back, and this one explains neither. Critically, it never says the result is a performance comparison against a random baseline, which is the key thing an agent must interpret when reading the response.

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?

With 12 parameters at 67% schema description coverage, the description adds almost nothing beyond the schema: "after its costs" hints fees are modeled, but stopLossPct, takeProfitPct, maxHoldHours, side, and market semantics are left entirely to the schema. Undocumented fields like stopLossPct and takeProfitPct receive no explanation in either place, so the description does not compensate for the coverage gap.

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?

"A rule on the recent past of any market the lab reads, against a coin flip, after its costs" obliquely conveys a historical backtest of a hypothetical trading rule benchmarked against a random 50/50 baseline net of fees, but it never uses a verb like preview, backtest, or simulate and never states what the tool produces. The contrast with the sibling opsin_perp_propose is only hinted at through "never signed," so an agent must infer that this is the unsigned dry-run counterpart.

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?

"Free, instant and never signed" implicitly tells the agent to try a rule here before committing it via a propose/sign path, which is real when-to-use signal. There is no explicit statement of when not to use it, no mention of opsin_perp_propose or opsin_market_preview as alternatives, and no prerequisites such as needing to read opsin_perps first.

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?

With no annotations, the description carries the full burden, and it does disclose a real lifecycle: immediate hashing (immutability), evaluation against future data, comparison against a coin-flip baseline, and signing on resolution, plus a soft rate limit. It omits whether proposals can be cancelled or amended, what happens to losing rules, and what a call returns.

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 compact sentence with the commitment semantics front-loaded and no filler. The trade-off is that 'against a coin flip' and 'A few a day' are oblique phrasings that cost more clarity than the brevity saves.

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 14-parameter creation tool with no annotations and no output schema, the description should at minimum orient the agent on the required fields and the resolution lifecycle. It gestures at the lifecycle but leaves the parameter surface and return behavior entirely undocumented.

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?

Fourteen parameters at 64% schema coverage, and the description explains none of them. It never mentions side, maxHoldHours, the 'when' condition list, stop/take levels, or funding thresholds, so the unlabeled stopLossPct, takeProfitPct and label fields get no help from prose either.

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 verb+resource pair is concrete: 'Preregister a rule' on a market the lab reads, committed as a hash and later resolved. That tells an agent this creates a forward-looking, verifiable prediction. It does not distinguish itself from opsin_market_propose or opsin_propose, and 'any market' obscures that this is the perp-specific variant.

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?

'Hashed now, measured on what comes next' implies the rule must be registered before the outcome exists (no lookahead), and 'A few a day' implies a rate budget. Neither is stated as an explicit rule, and no sibling alternative is named, so an agent must infer when to pick this over the preview or market-propose tools.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether this is read-only or mutating, whether authentication or permissions are required, whether there are side effects, or what the response shape is; the 'coin flip' phrasing does not clarify behavior.

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?

The description is two sentences and front-loads 'Market trials,' with the sibling pointer placed at the end. The parenthetical market list is long but bounded, and there is no obvious filler, though the second clause is cryptic rather than clarifying.

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?

With no annotations, no output schema, and no parameters, the description must fully orient the agent. It gives a market scope and one sibling exclusion, but omits what calling the tool actually does and what it returns, leaving the agent unable to invoke it with confidence.

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?

The tool has zero parameters, so there is no parameter meaning for the description to add. The empty schema is fully described by the structural definition, and the description neither helps nor harms parameter understanding.

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 labels the resource as 'Market trials' and describes a broad market scope, but never states a concrete action such as list, read, or measure. Phrases like 'every belief measured... against a coin flip' and 'what each market's rules can ask about' are jargon-heavy and leave the core purpose ambiguous, though the final sentence does distinguish it from opsin_markets for Elysium launches.

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 only usage signal is the exclusion 'Launches on Elysium are in opsin_markets.' There is no guidance on when to use this tool, what preconditions exist, or how it relates to alternatives like opsin_perp_preview, opsin_market_preview, or opsin_markets beyond that single split.

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?

With no annotations, the description carries the full burden, and it does disclose the most important trait: the call is asynchronous and returns only a proposal id, with the verdict deferred to cycle publication. It says nothing about whether a proposal can be edited or withdrawn, whether submissions are rate-limited, or what permissions the lab requires, which are significant gaps for an unannotated write-style tool.

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, front-loaded with the verb and resource, then the kind taxonomy, ending with the return contract. The long parenthetical kind list is dense but each gloss disambiguates a distinct enum value, so little could be cut without losing routing information.

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 an 11-parameter, kind-polymorphic tool with no output schema, the description supplies the return shape (proposal id), the async verdict model, and the kind-to-parameter mapping an agent needs to fill the schema correctly. The residual gaps are secondary fields like label and base_thinking, whose schema notes are adequate on their own.

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 coverage is 82%, so the baseline is 3, but the description genuinely adds mapping semantics: it ties each kind to the parameter it consumes (line/block/example use text, skill uses name plus text, stack uses two to four lines in order, setting uses thinking and effort, route uses model). Only label and base_thinking are left entirely 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?

The description states a concrete verb and resource ("Propose a part of an AI agent") and then enumerates all eight part kinds with a gloss for each, so an agent knows exactly what can be submitted. It does not explicitly distinguish itself from the similarly-named siblings opsin_market_propose and opsin_perp_propose, leaving the domain split to inference from the names.

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 rather than stated: "Returns the proposal id; the verdict arrives when its cycle publishes" hints that opsin_cycle and opsin_verdict are the follow-up tools, but neither is named as an alternative or next step. Nothing tells the agent when to prefer opsin_propose over opsin_ask, opsin_market_propose, or opsin_perp_propose, and no prerequisites or exclusions are given.

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?

No annotations are provided, so the description carries the behavioral burden. It usefully discloses that answers come from signed verdicts, that model matching only recognizes paraphrased order and flags that match, and that pasted content is not stored, though permissions, error behavior, and rate limits are not stated.

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?

The description is three tightly packed sentences, with the main operation and output categories front-loaded before the provenance and privacy caveats. The phrasing around 'same order in other words' is somewhat opaque, but there is little wasted text.

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 two-parameter read tool, it covers the output categories and a key non-storage guarantee, but it omits explicit usage guidance and leaves terminology such as 'signed record' and 'datasheet' unexplained. With no annotations and no output schema, more operational context would be needed for full completeness.

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 coverage is 50%: the agent parameter is documented in the schema, while the prompt parameter is not. The description adds that prompt is a whole pasted multi-line text and that pasted content is not stored, but it does not clarify prompt formatting, size limits, or agent identifier expectations.

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 definition names a specific operation: reading a whole prompt against the signed record, with measured lines, their actions/datasheets, and never-measured lines returned. It is clear enough to distinguish the core operation, but it does not explicitly differentiate itself from siblings such as opsin_ask or opsin_verdict.

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 says what the tool does but gives no when-to-use conditions, prerequisites, or explicit alternatives. An agent must infer whether to call this instead of opsin_ask, opsin_verdict, or another sibling.

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?

With no annotations, the description carries the full burden. Enumerating what the snapshot includes is a useful behavioral signal that this is a read-only overview, but it never states read-only semantics, whether data is live or cached, or what freshness guarantees apply.

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 sentence with a compact colon-list structure, no padding, and no redundant sentences. Domain jargon like 'light budget' and 'lab' weakens immediate clarity but does not affect length or efficiency.

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?

Because there is no output schema, the description usefully doubles as a return-content summary, listing the five categories an agent will see. Still missing are freshness expectations and a clear boundary against the more specific sibling tools, which matter for an overview tool.

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?

The tool takes zero parameters, so there is no parameter meaning for the description to add. Baseline 4 applies; the schema coverage signal is moot with an empty input 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?

The description conveys that this is a current-state snapshot and enumerates its contents (running cycle, queue, light budget, verdicts), which is more than a restatement of the name. However, 'The lab right now' is metaphorical rather than a concrete verb+resource, and nothing distinguishes it from siblings like opsin_cycle or opsin_verdict.

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?

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives. Given that opsin_cycle and opsin_verdict exist as apparent siblings, an agent gets no help deciding when a full status snapshot is preferable to querying one of those specifically.

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?

No annotations are supplied, so the description must carry the burden; 'List' implies a read-only, side-effect-free operation and the phrase 'what 'exact' means' signals that semantic clarifications are returned. It says nothing about output shape, size, or caching, which matters given the absence of an output schema.

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, but the embedded quote around 'exact' is opaque out of context and slightly reduces immediate comprehension for a first-time caller.

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-parameter, no-output-schema listing tool, the description tells the agent the three categories of content returned, which is close to sufficient. A short note on response form or typical size would fully close the gap.

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?

The tool takes zero parameters, so the baseline of 4 applies; there is no parameter semantics to explain and the description correctly spends no words on inputs.

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 ('List the task suites') and enumerates the three things returned, which separates it from siblings like opsin_markets and opsin_perps. It never names an alternative explicitly, so differentiation is inferential rather than stated.

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 only implied: the mention of 'the part kinds you can propose' hints this is a discovery step before opsin_propose, but there is no explicit when-to-use, when-not-to-use, or named alternative. An agent must infer the workflow position.

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?

No annotations are supplied, so the description must disclose operational behavior. It explains how a returned verdict can be verified, but omits whether this is a read-only retrieval, what permissions are needed, what happens for an unknown id, and whether side effects occur.

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?

The description is two tight sentences with no filler, and the verification instruction is front-loaded. It is concise, though the opening noun phrase could better establish the tool's action before giving verification mechanics.

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?

With no output schema and no annotations, the description carries the full burden of explaining the operation and return value. It gives useful verification mechanics but does not explain what the tool actually returns for an id or how the canonical JSON body, digest, and signature are structured.

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?

The sole required parameter, id, is not mentioned in the description, and schema description coverage is 0%. The description does not explain whether id selects a verdict, which entity it identifies, or how it relates to the returned digest and signature.

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 names an artifact ('A signed verdict') and explains how to verify it, but never states an action such as retrieve, fetch, or verify by id. It largely restates the resource implied by the tool name and does not clearly distinguish its purpose from siblings like opsin_ask or opsin_status.

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?

There is no explicit guidance on when to use this tool, when not to use it, or which sibling tool is the alternative. The description provides cryptographic context but leaves usage selection entirely to inference from the tool name.

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