Premiss

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

Annotations already declare non-read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real context beyond that: the save is private, it returns code and revision, and notably 'saving does not run a backtest', which prevents the agent from expecting backtest output.

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 tight sentences, front-loaded with the core action and scope, then the input modes, then the side-effect clarification. No filler and no repetition of schema or annotation content.

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?

Covers the complex parts an agent needs: dual input paths, the package-format compatibility, and the fact that no backtest is triggered. Output schema exists so return values needn't be detailed, though the description adds that anyway. Missing only minor points such as whether files and template are mutually exclusive or whether name must be unique.

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 only 14%, so the description has to carry the load. It clarifies the files-vs-template alternative and the shape of files ('strategy.py plus helper modules'), but leaves symbol, interval, name, and the four required rules fields (watches/buys/sells/safety) unexplained.

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 ('Save a new private strategy') plus scope ('any Premiss-supported market and timeframe'), and the word 'new' implicitly separates it from the sibling update_strategy. An agent can pick between the two without opening either schema.

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 clear routing between the two input modes ('Accepts either files ... and rules, or a convenience template'), which is the main usage decision for this tool. It stops short of an explicit when-not or a direct comparison against update_strategy/start_backtest.

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, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds that data limitations are surfaced, which is genuine behavioral context, but says nothing about rate limits, auth, error behavior on unknown ids, or whether missing data is returned as null vs omitted.

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 the verb first and no filler; every clause maps to a distinct piece of returned information. It is efficient, though terse enough that it forgoes routing guidance it could have carried in the same sentence.

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?

An output schema exists so return values need no elaboration, and annotations carry the safety profile, which lowers the bar. Still missing is the one thing an agent needs operationally: where the market id comes from (search_markets) and how to interpret a failure for an unsupported market.

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?

One required parameter with 0% schema description coverage, so the schema does no work here. The description's phrase 'for a market id' is the only signal that the string is an identifier rather than a free-text name, and it gives no format, length, or provenance (e.g., obtained from search_markets), leaving the agent to guess.

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 verb ('Return') and a precise payload (supported timeframes, available history, data limitations) scoped to a market id. It is clearly distinguishable from search_markets in intent, but it never names or contrasts a sibling explicitly.

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: an agent can infer this is a pre-flight metadata check before a backtest, but the description states no when-to-use condition, no prerequisite, and no alternative. It neither says 'call this before start_backtest' nor warns against using it in place of search_markets.

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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered; the description adds useful scope boundaries by naming the write/research operations it will NOT perform. It does not describe pagination or refresh behavior, but for a static capability listing that is minor.

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, positive capability statement front-loaded, followed by the exclusions. Every clause earns its place with 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?

An output schema exists, so the description need not explain return values, and with zero parameters the only remaining question is scope — which the exclusions answer. It is fully sufficient to call correctly, with only minor room to state a positive 'use this first to discover tools' trigger.

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 semantics to explain and the baseline of 4 applies. Schema coverage is 100% and additionalProperties is false, leaving nothing for the description to compensate for.

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 (read) and a specific resource (this connection's available tools and supported research coverage), which is a distinct resource from every sibling tool. It is clear what the agent gets, though it does not explicitly name a sibling or contrast itself with one.

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 explicit negative scope — 'does not read account data, save research, or run a simulation' — which rules out the neighboring sibling operations (list_research, save_research_note, start_backtest). Usage context as a discovery/introspection call is clear, but no positive 'call this when...' trigger is stated.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description goes beyond them by disclosing the data-minimization boundary (excludes email, birth date, billing, exchange accounts), which usefully stops an agent from fishing here for user PII.

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 tight sentences: the first gives the purpose and selection scope, the second gives the returned shape and the exclusions. Front-loaded, zero filler, every clause carries 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?

With an output schema present, return-field detail need not live in the description, and annotations cover behavior; a zero-param read tool needs little more. The exclusions sentence adds the one thing the structured fields don't convey, leaving only minor mapping detail (account id vs. workspace label) to the output schema.

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 nothing for the description to disambiguate — the baseline of 4 applies. The description correctly implies the connection itself selects the identity, with no caller-supplied arguments needed.

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 precise verb ('Read') and resource ('stable identity and workspace selected for this connection'), and adds scope qualifiers ('stable', 'for this connection') that pin down exactly which identity is returned. No sibling tool competes for this purpose, so an agent can route to it unambiguously.

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: an agent infers it should call this when it needs to know which account/workspace the connection is bound to. There is no explicit when-to-use statement, no prerequisites, and no alternatives named (none exist among the siblings, so the cost is low).

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 safety profile (readOnly, idempotent, non-destructive, closed world), and the description adds genuinely useful context beyond them: the code is immutable, page size is not a history cap, paper data needs a separate permission, and saved code is user-authored content. That is substantive behavioral disclosure.

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 with no filler; the core capability is stated first and the constraints follow. Slightly compressed wording but 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?

An output schema exists so return shape need not be explained, and the description covers pagination, permissions, and content provenance. It is nearly complete for a read tool, with only the cursor naming mismatch and absence of alternative-tool routing as gaps.

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 0% schema description coverage the description must carry the load, and it does explain the 'kind' variants, the pagination cursor concept, and clarifies that 'limit' is a page size rather than a history cap. Minor mismatch: it refers to 'next_cursor' while the actual parameter is 'cursor', and run_id is left unexplained, but overall it compensates well.

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 specific verb+resource: reading the tested code package, trades, or equity points for an owned run, and names the 'kind' variants explicitly. It is distinguishable from siblings like get_run_report, though it does not name that sibling as an alternative.

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 implies when to use the tool (reading code, paging trades/equity) and adds a real prerequisite (separate paper:read permission for paper data), but never states when to prefer it over get_run_report or other read tools. Guidance is present but inferred rather than explicit.

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?

Beyond the readOnlyHint/idempotentHint/destructiveHint annotations, it discloses the auth requirement (paper:read), the conditional content (tested market, interval, revision, rules 'when verifiable'), the paired buy-and-hold baseline for historical plugin runs, and the labeling behavior for legacy runs. That is substantive behavioral context an agent cannot get from the annotations.

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?

Five short sentences, purpose front-loaded, no filler. The return-content detail is slightly redundant given an output schema exists, but each sentence still carries a distinct fact.

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-parameter read tool with an output schema and full annotations, the description covers permissions, scope exclusions, conditional output, and edge-case handling. An agent has everything needed to decide and invoke 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 0% and run_id has no description in the schema, so the description must carry the load. It conveys only that the id scopes to 'one run in the connected workspace' and nothing about format or provenance. Adequate but thin for a 0%-coverage parameter.

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 (read) and resource (status and bounded performance report for one run) with explicit scope ('in the connected workspace'). The closing line 'Does not return raw market feeds' cleanly separates it from the data-fetching sibling get_run_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?

Gives real usage conditions: paper reads require paper:read, and the tool does not start, stop, qualify, or modify a bot. It does not explicitly name get_run_data or another sibling as the alternative, so routing still requires inference, but the when-to-use context is clear.

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, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing that the return is a full Python package and flagging code/comments as user-authored content, which is a meaningful caution for an agent consuming untrusted text. It stops short of stating auth requirements or behavior when the strategy_id does not exist.

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 tight sentences with the core action front-loaded and no filler. The 'Code and comments are user-authored content' note earns its place as a safety-relevant caveat.

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?

An output schema exists, so return-value documentation is not strictly required, yet the description still summarizes the payload shape usefully. Combined with annotations covering the safety profile, an agent has nearly everything needed, with only parameter sourcing left implicit.

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 strategy_id parameter has only type and length constraints, so the description must carry semantic weight. It implies the identifier selects 'a saved strategy in the connected workspace' but adds no format, provenance, or how-to-obtain guidance beyond that.

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 a saved strategy's current revision and human-readable rules') and clarifies the payload is a complete Python package. It is clearly distinct from create_strategy and update_strategy by verb, though it never explicitly names those siblings.

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 by 'for review or editing,' which hints at a read-before-update workflow, but there is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives such as get_strategy_guide or update_strategy.

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, idempotentHint and destructiveHint=false, so safety is covered. The description adds real content beyond that: it enumerates what the guide covers (package format, on_bar API, execution semantics, example) and scopes the engine's applicability, which tells the agent what it is getting.

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 concrete deliverable and followed by scope context; no filler. Slightly dense but every clause carries 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?

An output schema exists, so return structure need not be explained. For a read-only, parameterless reference tool the description covers purpose, content scope and applicability adequately; only explicit routing guidance versus sibling tools 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline for a no-param tool applies. The description correctly adds no spurious parameter-like detail.

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 ('Read') and a specific resource (Premiss's Python package format, on_bar API, execution semantics, example), so an agent knows this returns reference material rather than strategy data. It is distinguishable from siblings like get_strategy (fetch a strategy) or create_strategy, though it never says so explicitly.

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 – 'Custom indicators, entry/exit logic, long/short strategies and risk rules use the same engine as the Premiss app' hints that this is the reference to consult before writing strategy code, but there is no explicit when-to-use, prerequisite, or comparison to get_capabilities/get_strategy.

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 safety profile (readOnly, idempotent, closed-world), yet the description adds real context: truncated excerpts are explicitly labeled, saved text is user-authored, paper runs need separate permission, and cursors are opaque. It does not describe page-size behavior or error cases, so it stops short of a 5.

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-loaded with the core action, then dense supporting facts in four short sentences with no filler. Slightly packed with tangential notes (user-authored content, permission caveat), but each sentence carries 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?

With an output schema present, return-value explanation is not required, and the description covers pagination model, search semantics, truncation labeling, and the permission gate. An agent could invoke it correctly; only page-size limits and kind-specific behavior are left implicit.

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 0%, so the description must carry parameter meaning. It clarifies query (matches titles) and cursor (opaque page positions), but says nothing about kind values beyond the enum or about the limit bounds (1-20) documented only in the schema, leaving two of four parameters thinly covered.

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 with enumerated scope: 'List a page of saved strategies, simulation runs, or research notes in the connected workspace,' matching the kind enum. It is easy to distinguish from siblings like get_strategy or save_research_note, though it does not name an alternative explicitly.

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 a prerequisite ('Paper runs require the separately approved paper:read permission') but no when-to-use-a-different-tool guidance. Nothing tells the agent when to prefer this over get_strategy or search_markets, so usage is only implied by the list scope.

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=false and idempotentHint=true with destructiveHint=false, so the bar is lower; the description adds genuine context that the note is private, user-authored, and not published or transmitted. It does not, however, explain the idempotency/request_key or revision behavior beyond the annotation.

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 action and scope, and every sentence carries information. 'The note is user-authored content' is mildly redundant but reinforces the privacy framing.

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 annotations covering safety/idempotency and an output schema covering the response, the remaining burden is parameter meaning. The description handles the evidence-reference parameters but is silent on the required idempotency key and revision parameter, leaving gaps for a 6-param write 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?

Schema description coverage is only 17% (just request_key), so the description must compensate. It usefully clarifies that strategy_id/run_id are optional 'exact owned' evidence references, but leaves the required request_key and the revision parameter unexplained, and adds nothing about title/note beyond the schema constraints.

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+resource (save a research note), states the scope (NEW, private, in the connected workspace) and the optional evidence-linking capability. It is clearly distinguishable from sibling tools like list_research or update_strategy without opening any schema.

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?

Implies usage (capturing user-authored research) and gives one exclusion via 'Does not publish or send it anywhere,' but never names an alternative tool or states when to prefer saving a note versus, say, updating a strategy. Guidance is implied rather than explicit.

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, idempotentHint, non-destructive and closed-world behavior, so the safety profile is fully covered. The description adds one useful scope constraint (no prices or candles in results), but says nothing about result ordering, pagination, or what the search matches against.

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, front-loaded with the verb and resource, with no filler. The only weak element is the opaque 'as Premiss' reference, which spends words without adding clarity.

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?

An output schema exists, so return-value documentation is not required, and annotations cover the safety profile. Still, for a search tool whose parameters are entirely undocumented in the schema, the description should have clarified query matching and result scope; the price/candle exclusion is a good start but not sufficient.

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 0% for all three parameters, and the description adds nothing about them. It never explains what 'query' matches (symbol, name, substring), why 'limit' is required despite a default of 20, or how 'asset_class' narrows the directory — leaving the agent to guess at the primary input semantics.

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 (Search) and resource (crypto, stock and ETF market directory), so the agent knows it discovers instruments rather than fetching data. However, the phrase 'the same directory as Premiss' references an external product name that carries no meaning on its own, and no sibling (e.g. describe_market) is named for contrast.

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 through the negative scope statement 'Does not return prices or candles', which hints that price data belongs to another tool such as describe_market, but no alternative is named and no positive condition ('use this when you need to resolve a symbol') is 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?

Goes well beyond the annotations by disclosing fixed simulation assumptions (10,000 capital, 10 bps fees, 1 bp slippage, next-bar-open fills), the absence of daily-test/history caps, and the exact shape of the acceptance receipt including run ids and poll_after_seconds. It also explains the idempotency mechanism more precisely than the idempotentHint annotation alone.

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?

Core purpose is front-loaded and most sentences earn their place by covering scope, fixed simulation defaults, receipt output, and idempotency. At eight sentences it is on the long side and the 'sandbox validation, supported markets, timeframes and date rules' clause is compressed to the point of being vague.

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 asynchronous job tool with an output schema, it covers the operationally critical points: idempotent recovery, the polling interval, and the fixed backtest assumptions. The one gap is that date-rule semantics for start_date/end_date are only alluded to rather than explained, which matters given the strict date pattern in the schema.

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 only 20% (request_key is the sole documented property), so the description must carry weight; it does clarify that an exact saved revision is required and that identical request_key plus inputs form the idempotent identity. It adds little on start_date/end_date beyond a vague reference to 'date rules' and nothing on strategy_id.

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 (queue a backtest) and resource (any saved strategy plus a matched buy-and-hold baseline), and scopes it to the connected workspace. It is clearly distinguishable from siblings like create_strategy, get_run_report and get_run_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?

Gives prerequisites (exact saved revision required, accepts custom code and existing app strategies) and implies the follow-up path via the poll_after_seconds status check. It never explicitly names an alternative tool or a when-not condition, so it falls short of full routing guidance.

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 flag destructive/idempotent/closed-world, and the description adds real value on top: it states the blast radius ('the submitted package replaces all existing files'), the protections in play ('active-run and shared-file protections apply'), the idempotency mechanism ('identical request_key and inputs identify the same write'), and a scope boundary ('does not change or start a bot').

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 sentences with the core action front-loaded and no filler; every sentence carries information. Slightly compact for a seven-parameter nested-schema tool, but nothing is wasted.

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 an output schema present, return values need no explanation, and the description covers the mutation's destructive scope, protections, idempotency, and bot-boundary. Gaps remain around the rules payload and failure/permission behavior, but it is sufficient to invoke the tool 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 coverage is only 14%, so the description must carry weight; it explains 'revision' as the exact current saved revision and 'files' as a full replacement, and 'Supports all Premiss markets and timeframes' loosely covers symbol/interval. But the rules object (watches/buys/sells/safety), strategy_id, and request_key receive no added semantics, leaving key parameters under-documented.

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 ('Replace the complete Python package and rules of an existing strategy'), and the word 'existing' plus 'exact current saved revision' cleanly separates it from the create_strategy sibling without needing its schema.

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 precondition 'using its exact current saved revision' implies this is for editing an already-saved strategy and hints at optimistic-concurrency usage, and 'does not change or start a bot' bounds the scope. However, no sibling is named and there is no explicit when-to-use-this-vs-create_strategy or when-not guidance.

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