leadbay_refine_audience

leadbay_refine_audience is a skill for Claude Code from leadbay/mcp. It costs 38 tokens per session (1,879 once invoked), scanned A, original, MIT.

A Leadbay skill for refining which kinds of companies appear as leads, using a plain-English description. Firmographics are basic company facts such as industry, size, or location; this skill focuses on the type of company, not its region.

In plain words
What is it for?
Use it to narrow Leadbay results with instructions such as focusing on hospitals that run their own IT department.
Why use it?
It prevents audience requests from mixing company-type criteria with unsupported or redundant country requirements, and asks for clarification when the request is unclear.

Skill for Claude Code

Written for Claude Code: a Claude Code plugin manifest.

Part of the leadbay plugin — 15 skills shipped together

Good fit Use it to narrow Leadbay results with instructions such as focusing on…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/leadbay/mcp/leadbay_refine_audience
View source ↗ leadbay/mcp
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add leadbay/mcp --skill leadbay_refine_audience
Clone the repo
git clone --depth 1 https://github.com/leadbay/mcp

Made for: Claude Code.

Or install leadbay, the plugin that ships this one along with the rest of its 15 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for leadbay_refine_audience

README.md
[![agentmods](https://agentmods.dev/badge/skills/leadbay/mcp/leadbay_refine_audience.svg)](https://agentmods.dev/skills/leadbay/mcp/leadbay_refine_audience)
Your own site
<a href="https://agentmods.dev/skills/leadbay/mcp/leadbay_refine_audience"><img src="https://agentmods.dev/badge/skills/leadbay/mcp/leadbay_refine_audience.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,879 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.01879
Opus 5 $0.00019 $0.00940
Sonnet 5 $0.00008 $0.00376
Haiku 4.5 $0.00004 $0.00188

Measured 6d ago against content hash 85c36c41be8e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

leadbay_refine_audience scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude-plugin/plugins/leadbay/skills/leadbay_refine_audience/SKILL.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Refine the Leadbay audience prompt to: <The refinement (e.g. 'focus on hospitals running their own IT'). Set to plain English. If not provided in the user's most recent message, ask once before proceeding.>

PHASE 0 — GATE: RESOLVE THE REGION, STRIP THE COUNTRY, THEN CLASSIFY (may end the run)

A refine prompt shapes the KIND of company, never WHERE it is. Before any tool call:

Step 1 — if a COUNTRY is named at all, find out which country this workspace serves, and do it FIRST. Every later step turns on whether the country I named is this workspace's own, and you cannot tell that from my message: "French hospitals across France" is a redundant clause on an FR backend and an unsupported ask on a US one, and the language I write in says nothing about it. Do NOT guess from the country I named, from my language, or from the fact that the request sounds plausible — strip first and you will have already decided, silently and possibly wrongly, that the country was redundant. Every Leadbay tool result carries the fact at _meta.region (us | fr | custom); if no call this session has returned one, call leadbay_account_status — read-only, writes nothing — and read _meta.region from it. custom means the backend's country is unknown: claim nothing about which country it holds. Only a place BELOW country level ("in Paris", "Texas") skips this step.

Step 2 — now strip, and do not stop. With the region known, if my instruction names this workspace's own country or a whole-country scope ("nationwide", "the whole US", "partout en France"), remove that phrase and KEEP THE REST. It is redundant, never a filter — but it is almost never the whole instruction. "Hospitals running their own IT nationwide" is a refinement about hospitals; "hospitals in Paris, France" is Paris plus hospitals. Losing the rest because a country rode along is the worse error of the two. A country that is NOT this workspace's own is not stripped — it is the whole answer, and Step 3 handles it.

Step 3 — classify what REMAINS, and act on every part of it:

  • Nothing remains (the country was the entire instruction) → STOP HERE. Call NOTHING. Do not continue to PHASE 1: leadbay_refine_prompt would overwrite my qualitative audience prompt and kick off an intelligence recompute to express a scope this workspace already has. Tell me there is nothing to set because the workspace already covers exactly that, offer the axes that do narrow an audience (sector, size, or a sub-country region / state / county / city), and end your turn.
  • A DIFFERENT country ("partout en France" on a US workspace) → STOP HERE too, but do not say "there is nothing to set" — that is false. The ask is UNSUPPORTED, not already-satisfied: this workspace holds only its own country's companies, so there are no leads there to scope to. Say so plainly, do not offer an unfiltered view as if it answered the request, and end your turn. If a qualitative part rode along with it, say it cannot be applied to a country that is not here either.
  • A supra-national scope ("EU-wide", "EMEA") → stop as well: name what the workspace covers and ask whether I want that instead, rather than assuming it.
  • A sub-country place ("prospects in Texas", "restrict to Indre-et-Loire") → a place is not a qualitative refinement: route it to leadbay_adjust_audience({locations: [...]}) and say why. If a qualitative part ALSO remains, continue to PHASE 1 with that part — do not drop half the request.
  • A qualitative refinement → continue to PHASE 1, passing the STRIPPED text and never the raw instruction.

One workspace = one country — a country name is NEVER a location filter. The admin-area index holds no country nodes, so "France" matches the commune of Francs and "United States" matches Statesboro: the call is silently fenced to one village and every conclusion from it is wrong. City AND country named? Keep the city, drop the country.

Read the full file on GitHub · 90 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 90 lines · 38 tokens per session scan A 85c36c41be8e

Subscribe to this mod's changes

leadbay_refine_audience is a skill published in the GitHub repository leadbay/mcp (0 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 1,879 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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