intake-relationship

intake-relationship is a skill for Claude Code, Codex from markmhendrickson/ateles. It costs 0 tokens per session (1,415 once invoked), scanned A, original, MIT.

An intake process that turns a prospect’s scattered materials—such as voice notes, emails, PDFs, videos, and links—into a navigable preview of their own work. It stores the extracted information in Neotoma, a linked knowledge graph, and prepares a shareable preview.

In plain words
What is it for?
Collecting a prospect’s source materials, extracting connected entities and information, creating a designed preview page, generating a guest share link, and preparing it for operator-approved sending.
Why use it?
It gives a prospect a concrete view of how their disconnected material can be organized, instead of explaining the product only in abstract terms.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/markmhendrickson/ateles/intake-relationship
Any agent
npx skills add markmhendrickson/ateles --skill intake-relationship
Clone the repo
git clone --depth 1 https://github.com/markmhendrickson/ateles

Made for: Claude Code, 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 intake-relationship

README.md
[![agentmods](https://agentmods.dev/badge/skills/markmhendrickson/ateles/intake-relationship.svg)](https://agentmods.dev/skills/markmhendrickson/ateles/intake-relationship)
Your own site
<a href="https://agentmods.dev/skills/markmhendrickson/ateles/intake-relationship"><img src="https://agentmods.dev/badge/skills/markmhendrickson/ateles/intake-relationship.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,415 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01415
Opus 5 $0.00000 $0.00707
Sonnet 5 $0.00000 $0.00283
Haiku 4.5 $0.00000 $0.00142

Measured 5d ago against content hash c43cc7f36404, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

intake-relationship 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.

.claude/skills/intake-relationship/SKILL.md · 37 lines

How it starts

The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.


name: intake-relationship description: Intake a contact's raw domain materials (voice notes, emails, PDFs, videos, links) and respond with a designed preview artifact that mirrors their own domain back to them as navigable structure. The first-touch onboarding motion for domain-rich human prospects — extract their materials into a Neotoma knowledge graph, render a rendered_page preview, mint a guest share link, and surface it for operator-approved sending. Owned/invoked by Sturnus. triggers: [intake-relationship, /intake-relationship, intake materials, prospect preview] user_invocable: true entity_id: ent_55b08c28fc379ceccb4f37d4

Purpose

Turn a prospect's scattered domain materials into a preview that shows them their own work transformed into navigable structure. Mirroring someone's tangle back to them as a clean, connected artifact converts far better than explaining the product — it demonstrates Neotoma's value (canonical graph + field-projection: author once, project many) on THEIR content, and activates them as a collaborator. Worked pattern (a movement-teacher pilot): 3 voice notes + 2 emails (3 PDFs, 4 videos) → ~20-entity domain graph → a designed rendered_page manual → a guest link → the prospect started sending source material to feed their manual.

When to use

  • Default first-touch for domain-rich HUMAN prospects (teacher, researcher, founder, practitioner with scattered knowledge).
  • NOT for developer/infra evaluators — they mirror codebase/data (use analyze / remember-codebase).
  • Trigger when a contact sends materials describing their domain/needs, or when Sturnus develops a domain-rich prospect.

Procedure

  1. INTAKE (any source): gws gmail (never the Gmail MCP), gws drive for attachment links, WhatsApp audio, links. Audio/video → transcribe (execution/scripts/transcribe_audio.py; for video, download + ffmpeg frame-extract to interpret before describing). PDF → download + pypdf text extract; note image-heavy pages. Store each as the right Neotoma entity (transcription/email) with provenance, REFERS_TO the contact + PART_OF the conversation. Store the contact as a person (enrich via Gmail/LinkedIn first; never a bare stub).
  2. EXTRACT THE DOMAIN GRAPH: model their domain as entities + relationships (register schemas if greenfield). Edges: PART_OF (membership), DEPENDS_ON (ordering/readiness), REFERS_TO (provenance). The relationships are the product — they dissolve the tangle. Every fact traces to its source artifact.
  3. RENDER THE PREVIEW (rendered_page): lead with their own organizing principle in their language; show worked depth in one area + a progress view (done/pending); include a connection map of illustrated cards (not abstract flowcharts) from real edges. Localize; warm; no brand-name concepts unless opted in. Illustrations as inline WebP data: URIs (self-contained, CSP-safe). ⚠️ REQUIRED accuracy spot-check: AI illustrations have defects (one pilot produced a three-arm pose, then a non-bound bind). Visually verify EVERY illustration before sharing; binds/twists/multi-limb poses are most error-prone — regenerate or fall back to a real video still. ⚠️ HOW TO RENDER — defer to the draft-rendered-page skill (the canonical authority for ALL rendered_page output, here and in any multi-page hub it grows into); invoke /draft-rendered-page or read its SKILL.md and follow its checklist rather than authoring CSS from scratch. Non-negotiables it enforces: light+dark mode via CSS-variable defaults + @media (prefers-color-scheme: dark) + html{color-scheme:light dark}; a pure-CSS Light/Dark/System toggle; host-template color overrides (th/pre/code/a with !important); no hardcoded inline color styles; WCAG-AA contrast in both themes; and the post-store verification fetch.
  4. MINT THE SHARE LINK: served at GET /entities//html; schema is guest_access_policy: submitter_scoped, so mint a guest_access_token scoped to the page and share …/html?access_token=. Use the Neotoma publish/share tool once neotoma#1619 ships. Keep the URL un-truncated (long query strings break on copy/paste). For a multi-page set (a hub + sub-pages), every inter-page link MUST carry the TARGET page's own access_token — guest tokens are page-scoped, not a session, so a bare /entities//html link 401s for the recipient. Build an {entityId: token} map, stamp every href, and verify zero tokenless /entities/.../html links on each live page before surfacing (per draft-rendered-page).
  5. SURFACE FOR OPERATOR APPROVAL — DO NOT AUTO-SEND: draft the outbound message (contact's language, warm, grounded) + the link; the operator sends (Sturnus boundary).
  6. ITERATE: on response with more material/feedback, loop to step 1 and extend the graph + page. Continued sending is the activation signal.

Read the full file on GitHub · 37 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. 5d ago First seen · 37 lines · 0 tokens per session scan A c43cc7f36404

Subscribe to this mod's changes

intake-relationship is a skill published in the GitHub repository markmhendrickson/ateles (6 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,415 tokens. 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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