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tokenpull_submit

Idempotent

Submit local token usage to the SigRank board in one call: reads session logs, computes the token cascade, and publishes with a codename. Token-only, no prompt content transmitted.

Instructions

Pull your LOCAL token usage from session logs AND publish it to the SigRank board in one call — the zero-paste flow. Reads the four canonical pillars (input, output, cacheCreate, cacheRead) per window from your local logs, computes the cascade, and submits each window to the board where it is re-scored server-side and tagged with the source platform. Requires a codename to publish; omit for a local preview only. Token-only — no prompt content is read or transmitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNoSubmit only this time window (default: all 4 windows). Use "7d" for recent activity or "all" for all-time ranking.
codenameNoOperator codename to publish under on the leaderboard (e.g. "Iron Lotus"). Required to submit — omit for local preview only.
platformNoSource platform to pull from (default: claude). Supported: amp, kimi, qwen, pi, openclaw, droid, codebuff, gemini, copilot, opencode, goose, kilo, hermes, devin, other, claude, codex, multi. 'multi' = combined cascade summed across all locally-detected platforms (needs 2+ active). 'devin' reads from ~/.local/share/devin/cli/sessions.db (SQLite, all windows). 'other' reads from a user-supplied JSON file (set SIGRANK_OTHER_PATH). Each platform reads its own session logs locally.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoError or skip reason if status is not ok
statusNoSubmission status
previewNo
server_responseNoServer-side response including new rank if accepted
Behavior5/5

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

The description adds significant behavioral context beyond annotations: it reveals that only token data (no prompt content) is read/transmitted, that it reads four pillars from local logs, computes a cascade, and submits with server-side rescoring. This aligns with idempotentHint and destructiveHint, and provides complete transparency.

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 a compact 5-sentence paragraph, front-loaded with the main action. Every sentence adds essential detail without fluff, making it efficient for an agent to parse.

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 tool's core behavior, parameter effects, and privacy guarantee. It could mention that results are published to SigRank board, which is implicit. With an existing output schema, the description is sufficiently complete for correct tool invocation.

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% with well-described parameters. The description adds extra value by explaining the effect of omitting codename (preview), specifying that 'multi' platform requires 2+ active platforms, and that 'devin' reads from a SQLite file. This goes beyond the schema's basic 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 clearly states the tool pulls local token usage and publishes to a board, using specific verbs like 'Pull' and 'publish'. It distinguishes itself from siblings like 'tokenpull' (likely only pull) and 'submit_paste' (manual submission) by describing the 'zero-paste flow' and specifying it reads four pillars and computes a cascade.

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 explains when to use a codename to submit vs. omit for preview, and allows filtering by window and platform. However, it does not explicitly state when not to use this tool (e.g., if only pulling is needed) or name alternative tools, though sibling names imply 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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