Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add cogni-work/insight-wave/plugin install cogni-portfolioWrote 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.
[](https://agentmods.dev/skills/cogni-work/insight-wave/portfolio-ingest)<a href="https://agentmods.dev/skills/cogni-work/insight-wave/portfolio-ingest"><img src="https://agentmods.dev/badge/skills/cogni-work/insight-wave/portfolio-ingest/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.
<a href="https://agentmods.dev/skills/cogni-work/insight-wave/portfolio-ingest"><img src="https://agentmods.dev/badge/skills/cogni-work/insight-wave/portfolio-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00088 | $0.03963 |
| Opus 5.5 | $0.00035 | $0.01585 |
| Sonnet 5.5 | $0.00018 | $0.00793 |
| Haiku 4.5 | $0.00009 | $0.00396 |
Grade A, and why
portfolio-ingest 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Upload Ingestion
Extract portfolio entities and institutional context from user-provided documents in the project's uploads/ folder. Supported file types: .md, .docx, .pptx, .xlsx, .pdf.
Core Concept
Plugin root resolution. Bash invocations below resolve the plugin root inline as ${CLAUDE_PLUGIN_ROOT:-$(ls -td "$HOME"/.claude/plugins/cache/insight-wave/cogni-portfolio/*/ | head -1)} — the first call works whether or not the harness injects $CLAUDE_PLUGIN_ROOT. Keep the inline form in every call; do not strip it.
Most users already have product information scattered across decks, spreadsheets, and documents. Ingestion bridges the gap between existing material and a structured portfolio in two ways:
- Entity extraction — turns unstructured documents into typed entities (products, features, markets) that the rest of the pipeline builds on.
- Context extraction — captures institutional knowledge (competitive intelligence, pricing benchmarks, strategic positioning, customer insights) as structured context entries that downstream skills use to generate sharper, company-specific output.
Entity extraction gives the user a head start on portfolio structure. Context extraction ensures the intelligence buried in strategy decks, pricing models, and win/loss reports doesn't get lost — it flows into propositions, solutions, competitor analysis, and every other downstream skill automatically.
Prerequisites
- An active cogni-portfolio project (
portfolio.jsonmust exist) - One or more supported files in the project's
uploads/directory - The
document-skillsplugin for non-markdown file extraction (docx, pptx, xlsx, pdf)
Workflow
1. Locate Project and Scan Uploads
Find the active portfolio project by searching for portfolio.json under a cogni-portfolio/ path (same approach as the portfolio-resume skill). If multiple projects exist, ask which one to use.
Scan uploads/ for supported files, excluding the processed/ subdirectory. If no files are found, tell the user the folder is empty and list the supported file types.
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.
- 1mo ago First seen · 276 lines · 88 tokens per session scan A 2a3dde40e9e1
portfolio-ingest is a skill published in the GitHub repository cogni-work/insight-wave (13 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 88 tokens to every session and 3,963 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-04.
Other skills, from other repositories
doc-reader
Read any common document/data file — PDF, Word (.docx), Excel (.xlsx/.xls), PowerPoint (.pptx), images (OCR), CSV/TSV, plain text, JSON/YAML/TOML, HTML/XML, and most source-code files. Use the readdocument tool.
xberg-extracting-tables
Use when extracting tabular data from PDFs, spreadsheets, or images. Covers layout-aware table detection, table model selection, output formats (markdown / JSON cells), and known limits.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
kordoc
A command-line and server tool for reading and creating Korean official documents, including HWP, HWPX, PDF, DOCX, and spreadsheet files. It can convert documents to Markdown and create or update HWPX files.
meta-multi-format-export-pack
From one piece of source content, render four deliverables: .docx report, .pptx slides, .xlsx data, and an HTML/PDF public version.
superlinked-docs
Offload document, image, and structured-output work to the Superlinked inference cluster: convert PDF/DOCX/PPTX/XLSX/HTML/scans to clean markdown, describe an image (caption + tags), or produce schema/grammar-constrained JSON off the cluster — instead of ingesting the file directly, which can reduce the tokens billed…