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Check Claim

boosthis_check_claim
Read-only

Holds a sentence an assistant is about to say (“checkout is faster now”) against what the running app actually did. Exactly one of four answers: supported, not supported by the measurements, cannot tell yet, or outside what Boosthis measures. Boosthis picks the comparison window; one named in the sentence is not used. It catches only a minority of wrong claims: the best measured result in this field is about one in six, and a claim kept vague is never caught at all. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesThe sentence to check, up to 240 characters. One carrying a credential or personal details is refused.
account_tokenNoOptional, the developer's account token: with it, a sentence the word match cannot place also gets a one-shot AI reading, which spends AI allowance.

TDQS

A4.5/5.0
Behavior5/5

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

With readOnlyHint and destructiveHint already in annotations, the description adds genuinely useful behavioral details: Boosthis chooses the comparison window, claims naming their own window are ignored, and the check has a significant known false-negative rate. The explicit 'Read-only' is redundant but consistent with annotations.

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

Conciseness5/5

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

The description is front-loaded with the core purpose and four concise sentences, each earning its place: purpose, verdicts, window-selection caveat, and reliability caveats. The final 'Read-only' is redundant with annotations but does not bloat the text.

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

Completeness5/5

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

For a two-parameter read-only tool with no output schema, the description is complete: it names the exact four answers, warns about the highest-risk failure modes, and the schema covers parameter constraints. An agent has enough to decide whether and how to call it.

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

Parameters3/5

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

Schema description coverage is 100%, and both parameters already carry clear descriptions, including claim length, refusal conditions, account_token behavior, and AI-allowance cost. The tool description itself adds no parameter-level meaning, so the baseline score of 3 applies.

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

Purpose5/5

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

The description states a concrete operation: hold a pending claim against what the app actually did, and enumerates the four possible verdicts. This is specific enough to distinguish it from siblings like boosthis_check_for_update, which concerns update status rather than claim verification.

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

Usage Guidelines4/5

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

The description supplies a clear trigger condition ('a sentence an assistant is about to say') and warns about limitations (vague claims are never caught, typical catch rate ~1/6). It does not name alternative tools or state explicit when-not-to-use conditions, but no sibling handles the same task.

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

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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target a distinct concern—alerts, budgets, jobs, promises, rules, crash risk, install/removal—and the descriptions are detailed enough to separate them. A few pairs, like verify_kit/verify_kit_install and recent_samples/session_summary, could be misselected without close reading, but they are not functionally identical.

Naming Consistency3/5

All tools share the boosthis_ prefix and use snake_case, which creates a recognizable namespace. However, the second part mixes noun-only names (alerts, budgets, jobs, snapshot, trend), verb-based names (get_rule, remember_promise, verify_kit), and one sentence-style name (what_should_i_look_at_next), so there is no consistent verb_noun convention.

Tool Count3/5

At 24 tools, this sits squarely in the borderline-heavy range for an MCP server. Each tool does have a distinct role, but the surface feels large, especially with several overlapping read-only diagnostics that could potentially be consolidated.

Completeness4/5

The set covers the main observability lifecycle well: install, verify, monitor, diagnose, check trends, and record promises. Minor gaps exist—like no way to mutate alert states or delete promises through the MCP—but these appear intentional and are documented as dashboard-side actions.

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