qualitative-filtering

qualitative-filtering is a skill for Claude Code from agentii-ai/agentii-investment-intelligence. It costs 39 tokens per session (2,154 once invoked), scanned A, original, Apache-2.0.

A qualitative investment-analysis method for studying company disclosures, earnings-call transcripts, management performance, key measures, and possible share-price catalysts.

In plain words
What is it for?
Use it to assess management plans, track key performance indicators, analyse earnings calls, gather evidence, and classify catalysts for an investment thesis.
Why use it?
It organises non-numerical evidence so an investment view is based on company history, operating results, and identifiable events rather than isolated claims.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the idea-generation plugin — 5 skills shipped together

Good fit Use it to assess management plans, track key performance indicators, analyse earnings calls, gather evidence, and classify catalysts for an investment thesis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering
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 agentii-ai/agentii-investment-intelligence --skill qualitative-filtering
Clone the repo
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence

Made for: Claude Code.

Or install idea-generation, the plugin that ships this one along with the rest of its 5 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 qualitative-filtering

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering/github.svg)](https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering)
Your own site
<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering/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 qualitative-filtering

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/qualitative-filtering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,154 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00039 $0.02154
Opus 5 $0.00019 $0.01077
Sonnet 5 $0.00008 $0.00431
Haiku 4.5 $0.00004 $0.00215

Measured 6d ago against content hash 85da4fbfeaba, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

qualitative-filtering 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.

plugins/vertical-plugins/idea-generation/skills/agentii/qualitative-filtering/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Methodology fused from professional trading and investment frameworks; all text is an original paraphrase.

Defaults

Parameter Default Value Rationale
catalyst_window_days 20-60 Trading horizon for active positions
kpi_trend_min_quarters 8 Minimum quarters of KPI history for trend analysis
mgmt_track_record_years 3 Management credibility requires 3+ years of guidance vs actuals
catalyst_min_impact 5% Minimum expected price impact to justify catalyst-driven trade

Preflight

Run canonical pre-flight per contracts/preflight.md. Propagate X-Agentii-Trace per contracts/x-agentii-trace-header.md.

Data Source Priority

  1. Qualitative methodology — references/qual-methodology.md (bundled MOP-KPI-Catalyst framework)
  2. Company disclosures — SEC filings (Business Description, Risk Factors, MD&A) via agentii MCP
  3. Earnings transcripts — search_documents(ticker={T}, form_type="earnings_call_transcript")read_source_outlineread_source_pages (citation prefix ect<N>; pages carry section_type in session_title and guidance/forward_looking/analyst_questions in labels)
  4. Strategy and case knowledge — search_investment_strategies + search_investment_cases + search_by_analogue

Methodology

Retrieval Scope

unstructured_document_search (earnings call transcripts + SEC disclosures)

Retrieval Strategy

Ownership & insider signals: search_institutional_holdings (top-10 holders + whale portfolios, direction=accumulating|reducing|new|exited) and search_insider_trades (Form-4 transactions with SEC URLs) are available as signal inputs.

Three-layer protocol from contracts/retrieval.md: the qualitative framework is bundled in references/qual-methodology.md. Earnings transcripts via search_documents(form_type="earnings_call_transcript")read_source_pages (Layer 1→3). Strategy frameworks and historical analogues via MCP knowledge tools. Detailed methodology and catalyst classification in references/qual-methodology.md.

Read the full file on GitHub · 135 lines

Files

What ships with it

2 files 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. 6d ago First seen · 135 lines · 39 tokens per session scan A 85da4fbfeaba

Subscribe to this mod's changes

qualitative-filtering is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (204 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 2,154 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 2026-09-05.

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