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hermoso-ai

Hermoso

Official
by hermoso-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

What to fix next, post by post

diagnose_posts
Read-onlyIdempotent

Diagnose what is wrong with a given social post and get the exact next edit to fix it, from hook to retention or offer issues.

Instructions

WHAT TO FIX NEXT, post by post — and the tool that fixes it. post_performance tells you which hook is AHEAD; this tells you what is WRONG with a given post and where the next edit goes. Under-distributed is A HOOK PROBLEM (change the opening: mine_angles, then list_hooks, then plan_variations). Seen but not held is A RETENTION PROBLEM (plan_variations to rebuild the middle against the same hook). Seen, held, and still not converting is AN OFFER PROBLEM. FOUR REFUSALS, AND YOU SHOULD REPEAT THEM RATHER THAN PAPER OVER THEM: (1) a post younger than ~24h is TOO EARLY and is never called a failure — it has not had its run; (2) a metric the platform does not publish is UNMEASURED, never zero — Facebook has published no post reach since 2026-06-15, Reddit publishes no impressions, and Google Business publishes nothing per-post at all; (3) below 5 measured posts on a channel there is no baseline of the brand's own, and the ONLY fallback is a published short-video hook floor that is NOT our measured number and does not transfer off TikTok/Instagram/YouTube — it is attributed in the output and you should attribute it too; (4) it does not always find a problem, and 'nothing here needs fixing' is a real answer rather than a failure to look. Hermoso cannot see conversions for an organic post — no channel reports installs or purchases against a post id — so the offer rung runs ONLY when the user tells you they are not converting and you pass converting:false. Print summary verbatim. Read-only, 0 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNohow many recent posts to diagnose (default 25, max 200). The baseline is always built from EVERY post recorded for the brand, never only these, so a bad month can never become its own definition of normal.
channelNorestrict to one channel: facebook, instagram, threads, x, linkedin, youtube, tiktok, reddit, pinterest
convertingNopass false ONLY when the user has told you these posts are getting seen and are not converting — it re-reads the ones that are earning their reach as an offer problem instead of a win. Omit when you do not know; we cannot measure it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.161

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description adds substantial behavioral context beyond them: the 24h 'too early' rule, the unmeasured-vs-zero distinction with dated platform examples, the <5-post baseline fallback and its non-transferability, the inability to see conversions, and the 0-credit cost. This is unusually rich disclosure.

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?

Long and heavy with all-caps emphasis, but front-loaded with the core purpose and problem-routing before the four refusals. Nearly every sentence carries actionable information; it is dense rather than padded, though the volume pushes against ideal brevity.

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?

No output schema exists, and the description compensates by stating that 'nothing here needs fixing' is a valid result, that summary must be printed verbatim, and that fallback baselines are attributed in the output. Complete for a diagnostic read tool.

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 description coverage is 100%, so the schema already documents limit, channel, and converting with detailed semantics (baseline built from every post, channel enum list, when to pass false). The description largely reinforces rather than extends this, so the baseline 3 applies.

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?

Opens with a specific verb+resource ('WHAT TO FIX NEXT, post by post') and immediately distinguishes itself from the sibling post_performance: 'post_performance tells you which hook is AHEAD; this tells you what is WRONG with a given post.' An agent can route between the two without opening either schema.

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 maps diagnostic outcomes to next actions (under-distributed → mine_angles, list_hooks, plan_variations; seen-not-held → plan_variations; seen-held-not-converting → offer problem), names the sibling it is not, and specifies the exact condition for the converting:false parameter. Nothing is left to inference.

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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