SCRIPTMASTERLABS — Robinhood RWA Intelligence

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

Annotations already declare this as a safe read-only, idempotent, open-world operation. The description adds meaningful context beyond annotations by specifying that it inspects official Robinhood event pages and that the values are observations, not SML forecasts.

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 concise sentences with the primary action and scope front-loaded. Every phrase adds useful context, including the important caveat that values are observations rather than forecasts.

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 simple one-parameter read tool with rich annotations, the description is largely complete: it explains what page is inspected, what kinds of values are shown, and that outputs are observations. The absence of error or permission details is minor given the read-only annotations and low complexity.

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 clarify the single event_url parameter. It does so minimally by indicating that the URL should point to one official Robinhood event page, but it does not describe URL format, validation, or examples beyond the schema's URI constraint.

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 and resource: 'Inspect one official Robinhood event page.' It also names the concrete contents inspected, and the singular scope distinguishes it from the sibling list tool prediction_list_markets.

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 'one official Robinhood event page' and the required event_url, suggesting it is for inspecting a known event rather than listing markets. However, it does not explicitly say when to use this versus prediction_list_markets or other siblings, nor does it state prerequisites or exclusions.

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 meaningful context beyond annotations: it clarifies that this is public evidence, involves no brokerage access, no order placement, and no synthetic odds.

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, purpose front-loaded, followed by a concise safety/scope clarification. Every sentence adds value and there is 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?

The tool is simple, annotations are rich, and no output schema exists, so the description does not need to explain return values. However, it leaves both optional parameters undocumented and does not clarify filtering behavior, which is a noticeable gap for an agent trying to invoke it 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 the description does not mention the 'limit' or 'category' parameters at all. The parameter names are somewhat self-explanatory, but with no schema descriptions the agent receives no guidance on category values, filtering behavior, or limits beyond the raw JSON 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?

The description uses a specific verb and resource ('List event markets') and scopes it to Robinhood's public prediction-markets pages. It is clearly distinguishable from the singular prediction_get_market sibling, though it does not explicitly name siblings or contrast behavior.

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 states what the tool lists but gives no explicit guidance on when to use it versus prediction_get_market or prediction_rank_attention. There are no exclusions, prerequisites, or routing cues beyond the general 'public evidence' framing.

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/openWorld, so the safety profile is covered. The description adds genuinely new behavioral context the annotations cannot convey: it returns partial or no rank instead of inventing attention scores when volume data is missing, which tells the agent how to interpret gaps in 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?

Two sentences, zero filler, with the scoping restriction front-loaded ahead of the failure-mode disclosure. Nothing repeats the title or annotations.

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 honesty policy is well covered, but with no output schema and no parameter documentation, the description never says what a 'rank' or 'attention' value looks like, whether results are ordered, or how partial results are represented. For a tool whose entire selling point is a scoring output, that leaves a real 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?

Schema description coverage is 0% for both parameters — limit and category appear as bare typed fields with only default/maximum/pattern. The description mentions neither parameter, so an agent gets no meaning for what 'category' values correspond to or how limit affects the ranking breadth.

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+resource (rank prediction-market attention) plus a hard scoping rule: only markets with an explicit public Robinhood volume signal. That distinguishes it from prediction_list_markets and prediction_get_market, which surface markets rather than ranking them, though no sibling is named 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?

The coverage constraint implies when the tool is appropriate (you want attention ranking and accept partial results), but there is no explicit when-to-use statement, no exclusion of alternatives like prediction_list_markets, and no guidance on choosing this over a snapshot-style 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?

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so safety is covered. The description does add non-obvious context beyond the annotations — namely that this tool sits in a paid/x402 path and returns a complete payload that upstream free calls do not — but it never clarifies cost, auth requirements, latency, or what 'premium' concretely implies. The added signal is real but murky.

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?

Only the final sentence is substantive. 'Premium intelligence.' is a fragment with no operational content, and the second sentence is meta-commentary about upstream pricing and 'SqueezeOS x402 purchase path' that is front-loaded ahead of the actual capability, burying the one useful clause.

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 does the minimum of naming the return categories (quote, multiplier, corporate actions, risk flags), but it does not describe their structure or what 'multiplier' means in this domain, nor does it explain the symbol input. For a single-parameter read tool whose annotations cover the safety profile, this is adequate but leaves real 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?

Schema description coverage is 0%, so the description carries full burden for the single 'symbol' parameter, and it never mentions symbol syntax, accepted formats (e.g. Robinhood stock-token ticker vs. underlying equity ticker), or case sensitivity. The word 'asset' in the return-value list only loosely implies the symbol identifies an asset; the agent must guess the format within the 1-16 character constraint.

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 never states a verb or the resource being acted on — 'Analyze' exists only in the name/title, and the body opens with the vague fragment 'Premium intelligence.' The third sentence does enumerate what the tool returns (asset data, reference quote, multiplier, corporate actions, risk flags), which lets an agent infer it produces a per-asset intelligence report, but the purpose is inferred rather than stated and there is no differentiation from siblings like rwa_compare_assets or rwa_market_snapshot.

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?

No when-to-use guidance is given, and no alternative is named despite five RWA siblings in the toolset. The closest thing to routing information is the claim that 'direct upstream MCP calls ... do not expose the complete paid payload,' which implies this is the fuller-coverage option, but that is a marketing hint rather than an explicit use condition.

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, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds only vague "Premium intelligence" and x402 paid-payload context, without clearly explaining whether this tool itself is paid, what the paid payload contains, or how observations affect behavior. It does not contradict the annotations, but it adds little actionable 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?

The first two sentences are marketing/upstream-payment context rather than tool-specific guidance, so they do not earn their place in a short description. Only the final sentence directly describes what the tool does, and the useful purpose statement is buried after promotional 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?

For a two-parameter tool with a complex nested observations object, no output schema, and 0% schema description coverage, the description is incomplete. It does not explain how observations are used, what the comparison returns, or what the "evidence-first opportunity engine" produces. The annotations cover safety but not invocation-critical semantics.

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 partially explains symbols by saying "two or more Robinhood Stock Tokens," which aligns with the schema's minItems=2. However, it says nothing about the observations parameter, which is a nested object with venue, bid, ask, source_url, observed_at, and liquidity_usd fields.

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 and resource: "Compare two or more Robinhood Stock Tokens." That is enough to distinguish it from list/analyze/snapshot siblings, though it does not explicitly name those alternatives. The opening marketing phrase adds noise but does not obscure the core purpose.

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 implies this tool is for comparing multiple tokens, but it gives no explicit when-to-use guidance versus siblings like rwa_analyze_asset or rwa_find_opportunities. There are no stated prerequisites, exclusions, or alternative selection criteria.

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, so the safety profile is covered. The description does add one genuinely behavioral note — that direct upstream calls return only the purchase path and not the full paid payload, implying a cost/premium tier — but it is phrased ambiguously and never says what the tool's output contains or how scoring is bounded.

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 sentences, but the first two are monetization boilerplate placed ahead of the only operational sentence, so the definition is not front-loaded. The space spent on 'Premium intelligence' and the x402 purchase path buys the agent nothing it can act on.

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, four undocumented parameters, and no explanation of what a scored 'opportunity' looks like, the description leaves the agent unable to predict results or fill optional inputs. For a read-only, open-world scoring tool this is well short of what is needed.

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% across four parameters, so the description must compensate and it largely does not. 'Supplied venue evidence' faintly maps to venue_observations, but symbol, stale_after_seconds, and minimum_liquidity_usd are never mentioned, leaving their semantics entirely to the JSON types.

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 only sentence describing actual work is 'Score a Robinhood Stock Token only from authoritative reference data and supplied venue evidence,' which gestures at scoring/ranking but never states what an 'opportunity' is or what the tool returns. The opening two sentences are about upstream MCP calls and an x402 purchase path, which describe the vendor's monetization rather than this tool's verb+resource, and nothing distinguishes it from siblings like rwa_analyze_asset or rwa_market_snapshot.

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 a single implied constraint ('only from authoritative reference data and supplied venue evidence') but no statement of when to call this versus rwa_analyze_asset, rwa_compare_assets, or rwa_market_snapshot. An agent has no basis for routing between the seven siblings from this text.

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 open-world, so the safety profile needs no restating. The description's only added behavior is that results come from an 'authoritative' source and constitute the canonical asset list, which is modest value beyond the structured fields.

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 the resource and the optional filter front-loaded; nothing is extraneous and nothing important is buried.

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 should hint at what an 'asset' record contains (address, chain, symbol, metadata) and whether the unfiltered call returns the full set. It establishes scope but not the return shape, which is the main missing piece for a discovery 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 0%, so the single 'symbol' parameter has no documented matching semantics. The description clarifies that filtering is optional and keyed on symbol, but says nothing about exact vs. partial matching, case sensitivity, or the effect of an unmatched symbol — leaving a real gap for the only input.

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 ... Stock Token assets') with a named data source ('Robinhood Chain', 'authoritative'), which separates it from analysis siblings like rwa_analyze_asset and rwa_compare_assets. It does not explicitly name those siblings, but the read/list scope is unambiguous.

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 phrase 'optionally filtered by symbol' implies the two call modes (full listing vs. single-symbol lookup), so usage is inferable. However, there is no explicit guidance on when to pick this over rwa_analyze_asset, rwa_market_snapshot, or the prediction listing 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description's one behavioral claim, that direct upstream calls do not expose the 'complete paid payload for free', hints at tiering or paywalling but never says what this tool actually returns, whether output is truncated, or whether the caller needs a purchase step, and the phrase 'without inventing venue liquidity' is unexplained.

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 actual purpose appears only in the third sentence, after two sentences of 'Premium intelligence' and upstream x402 purchase-path talk that reads like promotional copy rather than tool guidance. Front-loading is inverted and the noise costs the reader without earning 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?

No output schema exists, so the description is fully responsible for conveying what a 'snapshot' contains (tokens, prices, liquidity?), yet it never describes the shape or contents of the result. Combined with an undocumented limit parameter and no sibling routing, an agent cannot confidently predict 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 0% and the single 'limit' parameter (default 10, max 25) is never mentioned in the description. With low coverage the description should compensate by explaining what is being limited (tokens? venues? rows?) and the ordering, but it adds nothing.

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 phrase 'Return a read-only snapshot of active Robinhood Stock Tokens' does state a concrete verb and resource, so the core action is recoverable. But it is buried behind two sentences of marketing/payment boilerplate and never distinguishes itself from siblings like rwa_list_assets or rwa_analyze_asset, leaving 'snapshot' undefined versus 'list'.

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 rwa_list_assets, rwa_analyze_asset, or rwa_compare_assets, which all operate on the same asset domain. The only guidance is an implicit contrast between 'snapshot' and analysis/listing, which the agent must infer.

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