enrich-company-and-contact-data

enrich-company-and-contact-data is a skill for Codex from evoelsewhere/evoflux. It costs 84 tokens per session (2,245 once invoked), scanned A, a copy of enrich-company-and-contact-data, Apache-2.0.

A workflow for completing and checking information about companies, contacts, leads, and potential customers. It compares known facts and signals with target-customer rules, while separating reliable information from uncertainty.

In plain words
What is it for?
Use it for company and contact research, industry and technology profiling, target-customer matching, list building, segmentation, territory scans, and sales-signal analysis.
Why use it?
It removes manual searching and reconciliation when building prospect lists or filling gaps in company and contact records. It helps show which prospects fit and what the available evidence supports.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is {Follow the instructions and output format/conditions in [Limitations and Improvements](../index/SKILL.md#limitations-and-improvements)}.

Good fit Use it for company and contact research, industry and technology profiling, target-customer matching, list building, segmentation, territory scans, and sales-signal analysis.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/evoelsewhere/evoflux
agentmods
npx agentmods add skills/evoelsewhere/evoflux/enrich-company-and-contact-data

Made for: Codex.

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 enrich-company-and-contact-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/evoelsewhere/evoflux/enrich-company-and-contact-data/github.svg)](https://agentmods.dev/skills/evoelsewhere/evoflux/enrich-company-and-contact-data)
Your own site
<a href="https://agentmods.dev/skills/evoelsewhere/evoflux/enrich-company-and-contact-data"><img src="https://agentmods.dev/badge/skills/evoelsewhere/evoflux/enrich-company-and-contact-data/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for enrich-company-and-contact-data

Your own site · 80×15
<a href="https://agentmods.dev/skills/evoelsewhere/evoflux/enrich-company-and-contact-data"><img src="https://agentmods.dev/badge/skills/evoelsewhere/evoflux/enrich-company-and-contact-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,245 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 100% copy Near-identical to another mod 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 $0.00084 $0.02245
Opus 5 $0.00042 $0.01123
Sonnet 5 $0.00017 $0.00449
Haiku 4.5 $0.00008 $0.00225

Measured 5d ago against content hash 072fb8571e9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

enrich-company-and-contact-data 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 5d 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.

Origin

This is a copy

100% identical to enrich-company-and-contact-data — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

app/agent/builtin_skills/sales/references/workflows/enrich-company-and-contact-data/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Enrich Company And Contact Data

Context-Gathering Intake

Whenever this skill asks for context, strongly prefer using the answers-ask-user-input skill and the ask_user_input tool over other tools such as request_user_input; otherwise ask directly in the conversation.

Prepare a sales person with a trusted, decision-ready view of companies or contacts: what is known, what is a strong match, what is still uncertain, and what action the data supports. This skill owns evidence resolution, ICP-fit and coverage comparisons, and source-grounded signal analysis; it does not own rep-work priority, outreach execution, or CRM writes.

Common Skill Instructions

MANDATORY: If not already in context, read and adhere closely to plugins/sales/skills/index/SKILL.md## Cross-Skill Best Practices.

Enrichment Ranking

Use this priority order when the request is broad or the working set is ambiguous.

  1. Explicit user-provided rows, domains, contacts, companies, ICP criteria, requested fields, or stated ranking rule
  2. The named CRM account set, territory, target list, or documented ICP that the user points to
  3. Entities that satisfy every hard filter, such as geography, industry, company size, technology, role, or seniority
  4. Entities with high-confidence identity resolution and enough comparable evidence to support the requested output
  5. Entities with a clear fit implication, reachable buying-team path, or source-grounded external signal
  6. Near matches and unresolved entities, clearly separated from qualified results

Do not silently broaden a supplied list into discovery, merge ambiguous entities, or rank by a criterion the user cannot inspect.

If the user asks to score or tier a list, keep the judgment limited to ICP fit, enrichment completeness, identity confidence, or defined signal strength. If the user asks which accounts to work now, where to focus, or what rep action deserves priority, route to prioritize-accounts.

Key Dependency Categories

These are particularly important for this workflow; use your best judgment to potentially include other data sources to improve quality.

Read the full file on GitHub · 175 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 5d ago First seen · 175 lines · 84 tokens per session scan A 072fb8571e9e

Subscribe to this mod's changes

enrich-company-and-contact-data is a skill published in the GitHub repository evoelsewhere/evoflux (7 stars, last pushed yesterday), licensed Apache-2.0. It adds 84 tokens to every session and 2,245 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to enrich-company-and-contact-data, differing in 0 lines, and is treated as a copy.

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