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eonik-ai

eonik-mcp

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get_context_ledger

Retrieves a context ledger to track interactions and data for auditing or reference.

Instructions

Everything the marketer has told eonik — durable brand truths (what 'working' really means, which customers are worth more, hard-won creative beliefs, economics), dated upcoming plans (sales/launches/seasonal), and recent verbatim corrections. The proprietary input no competitor or general agent can scrape. ALWAYS read this before giving strategic advice — it overrides generic best practice. Facts, verbatim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses the source authority (what the marketer told eonik), the types of content (truths, plans, corrections), currency signals (dated, recent), and its role as an overriding source. It stops short of describing exact output formatting or update mechanics, but for a zero-parameter read tool this is strong behavioral 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 compact and front-loaded with purpose, then uses brief illustrative examples and a prioritized usage directive. Every sentence adds value, with no redundant fluff or repetition of the tool name.

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?

For a parameterless retrieval tool with no output schema, the description sufficiently covers what the ledger contains, why it matters, and when to use it. It could be even more complete by explaining how it relates to sibling context tools like get_brand_context or get_account_memory, but it remains highly actionable on its own.

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?

The tool has zero parameters, so there are no parameter semantics to clarify. The baseline of 4 applies, and the description compensates by clearly defining the scope of what will be returned.

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 identifies the resource (a proprietary marketer-supplied ledger) and its contents: durable brand truths, dated plans, and recent corrections. It also distinguishes this tool from generic alternatives by stating it is the proprietary input no competitor or general agent can scrape and that it overrides generic best practice.

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 gives explicit usage guidance: 'ALWAYS read this before giving strategic advice' and notes that it overrides generic best practice. It does not name sibling alternatives or formal when-not-to-use cases, but the unconditional 'ALWAYS' provides clear context for when this tool should be selected.

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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