01-vc-pipeline-pull

01-vc-pipeline-pull is an agent for Claude Code from assafkip/kipi-system. It costs 23 tokens per session (444 once invoked), scanned A, original, MIT.

An optional data agent that retrieves active investor pipeline records from an external application programming interface (API), a service for exchanging data between systems.

In plain words
What is it for?
It fetches investors who are not marked as passed or lost and records their firm, status, tier, last contact, and possible introduction path.
Why use it?
The pipeline can continue when the external service is missing or unavailable because the agent records a skip or error instead of stopping the process.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Good fit It fetches investors who are not marked as passed or lost and records their firm, status, tier, last contact, and possible introduction path.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/assafkip/kipi-system/01-vc-pipeline-pull
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.

Clone the repo
git clone --depth 1 https://github.com/assafkip/kipi-system

Made for: Claude Code.

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 01-vc-pipeline-pull

README.md
[![agentmods](https://agentmods.dev/badge/agents/assafkip/kipi-system/01-vc-pipeline-pull/github.svg)](https://agentmods.dev/agents/assafkip/kipi-system/01-vc-pipeline-pull)
Your own site
<a href="https://agentmods.dev/agents/assafkip/kipi-system/01-vc-pipeline-pull"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/01-vc-pipeline-pull/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 01-vc-pipeline-pull

Your own site · 80×15
<a href="https://agentmods.dev/agents/assafkip/kipi-system/01-vc-pipeline-pull"><img src="https://agentmods.dev/badge/agents/assafkip/kipi-system/01-vc-pipeline-pull.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 444 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00023 $0.00444
Opus 5 $0.00012 $0.00222
Sonnet 5 $0.00005 $0.00089
Haiku 4.5 $0.00002 $0.00044

Measured 6d ago against content hash 6af4cde99568, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

01-vc-pipeline-pull scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

2. Curl the pipeline API: `curl {{VC_PIPELINE_URL}}`
q-system/.q-system/agent-pipeline/agents/01-vc-pipeline-pull.md · 54 lines

What it actually says

Agent: VC / Investor Pipeline Pull (OPTIONAL)

You are a data-pull agent. Your ONLY job is to fetch investor pipeline data and write it to disk.

OPTIONAL AGENT

This agent is optional. If no VC pipeline API is configured ({{VC_PIPELINE_URL}} is not set or returns an error), write a graceful skip and exit. The pipeline will continue without this data.

Reads

  • Nothing. This agent fetches from a live API.

Writes

  • {{BUS_DIR}}/vc-pipeline.json

Instructions

  1. Check if {{VC_PIPELINE_URL}} is configured. If not set, write skip output and exit:

    {"skipped": true, "reason": "no_vc_pipeline_configured", "date": "{{DATE}}"}
    
  2. Curl the pipeline API: curl {{VC_PIPELINE_URL}}

  3. If the API returns an error or is unreachable, write {"error": "api_unavailable", "date": "{{DATE}}"} and exit. Do NOT halt the pipeline - this agent degrades gracefully.

  4. For each investor entry, extract: name, firm, tier, status, warm_intro_path, last_contact

  5. Filter to entries where status is NOT "Passed" and NOT "Closed Lost"

  6. Write results to {{BUS_DIR}}/vc-pipeline.json:

{
  "date": "{{DATE}}",
  "active_count": 0,
  "vcs": [
    {
      "name": "...",
      "firm": "...",
      "tier": "A|B|C",
      "status": "...",
      "warm_intro_path": "...",
      "last_contact": "YYYY-MM-DD"
    }
  ]
}
  1. Do NOT analyze or interpret. Just pull and structure.

Token budget: <1K tokens output

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 · 54 lines · 23 tokens per session scan A 6af4cde99568

Subscribe to this mod's changes

01-vc-pipeline-pull is an agent published in the GitHub repository assafkip/kipi-system (110 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 444 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other agents, from other repositories

gtd-project-manager

Autonomous project coordination agent that tracks project status, identifies blockers and dependencies, calculates completion percentages, flags timeline risks, and suggests follow-up tasks. Proactively escalates blockers older than 7 days. Invoked by ai-task-executor for :AI:pm: tagged tasks.

datacore-one/datacore · 0 tokens

create-space

Scaffold, validate, and repair Datacore team/personal spaces. Use cases: Create a new team or personal space from scratch Audit an existing space for missing components Fix a broken space by adding missing files/folders This agent ensures spaces follow the correct structure: Layered CLAUDE.md (base + space layers) GTD…

datacore-one/datacore · 110 tokens

module-registrar

Register new modules in the Datacore ecosystem. Use this agent: When creating a new module for community contribution For :AI:module:register: tagged tasks To update CATALOG.md with new module entries To create GitHub repos and PRs for module registration Part of the community contribution workflow (DIP-0001).

datacore-one/datacore · 78 tokens

scaffolding-auditor

Audit spaces against DIP-0003 scaffolding requirements. Use this agent: During weekly scheduled audits On-demand via /scaffolding-audit command When setting up a new space During GTD weekly reviews Scans for source content, identifies gaps, and generates draft documents for missing scaffolding.

datacore-one/datacore · 73 tokens

social-intel-writer

Executes an approved intel routing plan from social-intel-analyzer — creates CRM entries, updates lists and landscapes, writes zettels, and adds GTD tasks. Writes files only; does not analyze content.

datacore-one/datacore · 49 tokens

tag-suggester

AI-powered tag suggestion for content. Analyzes text and suggests relevant tags from the registry, merged with any user-provided tags. Called by knowledge-extractor, session-learning, gtd-inbox-processor.

datacore-one/datacore · 48 tokens