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SLSBMB AI

by com.slsbmb
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Read a published AI Outreach Playbook

get_example_playbook
Read-onlyIdempotent

The complete published AI Outreach Playbooks: Revopush (developer infrastructure), LeadToCall (sales software) and SLSBMB AI's own fundraising playbook. Without arguments: every published playbook, then Revopush's goal, audience estimate and audiences; with playbook: that playbook; with audience_number: that audience's research, why the sequence works, the current opener, two follow-ups and targeting. Use it to show what a playbook contains before anyone buys.

Input Schema

NameRequiredDescriptionDefault
playbookNoWhich published playbook to open: revopush (default), leadtocall or slsbmb-fundraising.
audience_numberNoThe audience to read in full, as numbered in that playbook's overview.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / playbook / description
      Previous value: -"Which published playbook to open; revopush (default)."New value: +"Which published playbook to open: revopush (default), leadtocall or slsbmb-fundraising."
    • changedInput schema / properties / playbook / enum
      Previous value: -[
-  "revopush"
-]New value: +[
+  "revopush",
+  "leadtocall",
+  "slsbmb-fundraising"
+]
  2. Changed2 schema fields changed
    • changedInput schema / properties / playbook / description
      Previous value: -"Which published playbook to open; slsbmb (default), revopush or masha."New value: +"Which published playbook to open; revopush (default)."
    • changedInput schema / properties / playbook / enum
      Previous value: -[
-  "slsbmb",
-  "revopush",
-  "masha"
-]New value: +[
+  "revopush"
+]
  3. Changed2 schema fields changed
    • changedInput schema / properties / audience_number / description
      Previous value: -"The audience to read in full, as numbered in the overview."New value: +"The audience to read in full, as numbered in that playbook's overview."
    • addedInput schema / properties / playbook
      Added value: +{
+  "description": "Which published playbook to open; slsbmb (default), revopush or masha.",
+  "enum": [
+    "slsbmb",
+    "revopush",
+    "masha"
+  ],
+  "type": "string"
+}
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered; the description adds the substantive behavior — precisely what content is returned for each argument combination, including follow-ups and targeting detail. It does not mention size/limits of the 'all playbooks' response, which is the one remaining behavioral gap.

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?

Front-loads the resource and the three playbook names, then enumerates the argument modes compactly with no filler. The sentence is long and dense, packing three invocation modes plus a use case into one run-on structure, which slightly hurts scannability.

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?

With no output schema, the description carries the return-value burden and does so for every argument mode, so an agent knows what it will get before calling. Combined with annotations covering the safety profile and a fully documented two-parameter schema, nothing essential is missing.

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%, so baseline is 3, but the description goes beyond the schema by tying each parameter to the shape of the result (playbook alone → that playbook; audience_number → research, why the sequence works, opener, two follow-ups, targeting). It does not state what happens if audience_number is supplied without a playbook (implicit default to revopush).

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?

Names the specific resource (three published AI Outreach Playbooks) and the verb (read/open), and enumerates exactly which playbooks exist. The closing line 'Use it to show what a playbook contains before anyone buys' positions it as a preview tool, distinguishing it from the pricing/purchase-oriented siblings.

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?

Gives explicit invocation modes: no arguments returns every playbook plus Revopush's goal/audience summary, a playbook argument returns that playbook, an audience_number returns that audience's research and sequences. It states the context of use ('before anyone buys') but names no alternative sibling tool or when-not condition.

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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