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Palmyr

by ai.palmyr

TikTok hook analysis

tiktok_hooks

Which caption openings actually earn views. Pass account_id or tag to measure YOUR accounts against their own median (0.001 USDC). Pass niche to report what is working in that niche across TikTok, needing no posting history — the answer for a brand-new account (0.05 USDC; tiktok_niches lists them, free). The two are never blended. Pass caption to classify a draft before posting. Paid per-action via x402 — the 402 challenge carries the exact price for the arguments you sent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoPool every account you own carrying this tag (0.001 USDC)
nicheNoReport the niche across TikTok — any word, resolved to the nearest known niche (0.05 USDC)
captionNoClassify this draft caption against the patterns in scope instead of returning the full report
paymentNobase64 x402 payment payload (X-PAYMENT); omit on first call to receive payment instructions
account_idNoMeasure this account you own (0.001 USDC)
recency_daysNoWiden or narrow the recency window (hooks decay; more sample, staler signal)
maturity_daysNoOnly count posts at least this old, so young posts don't drag the median

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full burden. It discloses pricing per mode, x402 payment flow with the 402 challenge carrying exact price, and the constraint that account and niche analyses are never blended. This goes beyond basic safety and adds meaningful operational context.

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 four sentences, front-loaded with the core purpose. Every sentence adds concrete information—modes, pricing, payment, and exclusions—without fluff or redundancy. It is dense but well-structured.

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

Completeness4/5

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

The description covers the main use cases, pricing, and payment flow, which is substantial for a tool with 7 parameters and no output schema. It does not specify return format, but given the descriptive nature, it provides enough context for correct invocation. Minor gaps remain around error handling or prerequisites, but these are not critical.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds significant semantic value by clarifying which parameters are alternative modes (account_id/tag vs niche) and the purpose of caption classification. It also links pricing to specific parameter choices. While it does not detail recency_days and maturity_days, these are already well-covered in the schema.

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 clearly states the tool analyzes caption openings that earn views. It distinguishes three distinct modes (account/tag, niche, caption classification) with specific verbs and outcomes, and differentiates from siblings like tiktok_niches and tiktok_analytics.

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

Usage Guidelines5/5

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

Explicitly explains when to use each mode: account_id or tag for measuring one's own accounts, niche for niche-wide reporting without posting history, and caption for draft classification. Also notes the two main modes are never blended and references tiktok_niches as a free listing of niches.

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

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct resource and action, clearly separated by domain prefixes (card_, email_, phone_, tiktok_). The only potential overlap is phone_read_messages vs wait_for_otp, but wait_for_otp is specifically for OTP extraction and is described as a replacement for hand-rolled polling, making the boundary clear. Status pollers are also domain-specific (card_status, tiktok_connect_status, tiktok_operation_status) and not ambiguous.

Naming Consistency5/5

All tool names follow a consistent snake_case convention with domain-first prefixes (e.g., card_buy, email_send, tiktok_post, phone_temp_number). Even less common names like wait_for_otp and i402_plan are descriptive and stylistically consistent. There are no mixed conventions or vague verbs.

Tool Count4/5

33 tools is above the typical 3-15 range, but the server covers a broad multi-domain purpose (cards, compute, domains, email, phone, TikTok, Twitter, orchestration). Each domain has a focused and coherent set, so the count feels justified rather than bloated. It is slightly high, but not excessively so.

Completeness3/5

Coverage is solid for email, phone, and TikTok, with full lifecycle operations (create, read, extend, delete/cancel where applicable). However, there are notable gaps: compute has only deploy (no list/stop/delete), domains have only check/register (no list/delete), and Twitter has only post (no read/manage). These gaps could force agents to work around missing resource management.

Resources