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Seo Competitors

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.7/5.0
Behavior5/5

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

The description adds meaningful behavior beyond annotations: persistence details (authenticated vs anonymous sessions, 24-hour retention) and scoping by identifier. This complements the idempotentHint and destructiveHint annotations without contradiction, informing the agent about memory lifetime and visibility.

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 compact yet information-dense: the first sentence states core purpose, followed by usage criteria, storage format, persistence details, and companion tools. Every sentence earns its place with no redundancy.

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 simple two-parameter write operation, the description covers purpose, key-value structure, retention behavior, scoping, and relationship to recall/forget. No output schema is needed for a store operation, and annotations cover safety traits. The tool is fully contextualized.

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 coverage is 100%, so the baseline is 3. The description offers examples of key-value content (e.g., 'resolved ticker', 'user preference') that reinforce the schema's parameter descriptions but do not add substantial new semantics beyond what the schema already provides.

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 saves data for later reuse across conversations or sessions, using a specific verb ('Save') and resource ('data... key-value pair'). It distinguishes itself from siblings by pairing with 'recall' and 'forget' and giving concrete use cases like resolved tickers or user preferences.

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?

It explicitly says 'Use when you discover something worth carrying forward' and provides example triggers. It also names complementary tools ('Pair with recall to retrieve later, forget to delete'), giving clear context on when this tool is appropriate relative to alternatives.

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

A3.8/5.0
Disambiguation2/5

Several tools are near-duplicates or easily confused: ask_pipeworx_beta is explicitly identical to ask_pipeworx, ai_visibility_check overlaps with scan_competitor_ai_presence, and polymarket_edges, polymarket_arbitrage, and bet_research all target opportunity discovery. While many tools are distinct, the boundaries between these clusters are unclear enough to cause misselection.

Naming Consistency4/5

The vast majority of tools use a consistent lowercase snake_case convention with descriptive noun/verb patterns (e.g., polymarket_edges, entity_profile, validate_claim, resolve_entity). Minor deviations like seo_domain_ranked_keywords and ask_pipeworx_beta are slightly off-pattern, but the overall style is predictable.

Tool Count2/5

32 tools is above the threshold where a set starts to feel bloated, especially for a server named "Seo Competitors". The count includes many unrelated subsystems—Polymarket betting, memory, subscriptions, and generic data routing—making it feel like a kitchen sink rather than a focused SEO competitor toolkit.

Completeness2/5

For a server claiming to support SEO competitor analysis, the surface is incomplete: it offers a keyword-ranking tool and AI visibility checks, but lacks standard competitor SEO capabilities like backlink analysis, rank tracking over time, content-gap analysis, or site audits. The broader data/query tooling is extensive, but it doesn't fill the gaps in the advertised domain.