Steledger

Register identity

register_identity

Idempotent

Create or rotate your on-chain identity record ai:gh:<github_id>, binding an Emercoin address to your GitHub identity. Requires a signed-in session (OAuth) and counts against the FREE-tier per-minute write limit. Run whoami first to confirm you are signed in; anchor memories under this identity afterwards with store_memory. Writes one NVS transaction paid by the gateway (you need no EMC); the record reads back as pending at once and confirmed after the next block (~10 min on average). Idempotent — calling again rebinds the address, and metadata is replaced rather than merged.

Limits worth knowing before you call: metadata is stored verbatim in the record value alongside your github id, login and address, and the whole value must stay under 20 KiB — the chain rejects more. Every 128 bytes of name plus value adds about 0.0001 EMC to the fee the gateway pays for you. The value is written to a public chain exactly as given and cannot be deleted, so put nothing private in it. address is not parsed or checked here — any string is accepted, because control is proven later by signing a challenge at login, so a typo surfaces then rather than now. Returns the record name and the transaction id.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`address`	Yes	Emercoin address to bind to your GitHub identity, e.g. 'EVfAn...'. It is the anchor for later signature login — you must control its key (control is proven when you sign a challenge at login, not here).
`metadata`	No	Optional JSON object stored verbatim in the identity record, e.g. {"agent": "my-bot", "url": "https://..."}. Omit if unused.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`txid`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 22, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations cover idempotence, read-only-ness, and destructiveness, but the description reveals far more: the record reads back as pending then confirmed, the gateway pays the fee, metadata is replaced rather than merged, data is public and undeletable, and address is not validated. This is rich behavioral context beyond what the annotations provide, and it contradicts none of them.

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

Conciseness4/5

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

The description is long, but every sentence earns its place by carrying operational constraints or workflow guidance. It is front-loaded with the core purpose, then logically progresses through prerequisites, effects, limits, and return value. It could be tightened slightly, but it is dense rather than padded.

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 write tool that triggers an on-chain transaction, the description covers prerequisites, settlement behavior, cost, data-sensitivity concerns, idempotency, validation gaps, and return value. The output schema exists, so return details do not need restatement. Nothing an agent needs to call this correctly is missing.

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

Parameters5/5

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

Although schema coverage is 100%, the description substantially enriches the parameters: it explains the 20 KiB value limit, the fee increase per 128 bytes, that metadata is stored verbatim and replaced, and that address is not parsed. These details materially change how an agent should construct arguments and go well beyond the schema's own descriptions.

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 names a specific verb action ('Create or rotate'), a precise resource ('on-chain identity record ai:gh:<github_id>'), and the binding mechanism ('bind an Emercoin address to your GitHub identity'). It is immediately distinguishable from siblings like read_record and store_memory, and even among write tools it defines exactly which record it owns.

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?

The description explicitly states prerequisites ('Requires a signed-in session (OAuth)'), tells the agent to run `whoami` first, and explains how this tool fits into a larger workflow ('anchor memories under this identity afterwards with store_memory'). It also warns about the per-minute write limit, which is exactly the kind of operational context an agent needs before invoking.

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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