What makes Skill notable?

1.7K downloads. Trust evidence available

How should Skill be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Skill

Deterministic-first portfolio analyzer — holdings, performance, Sharpe + Sortino, FRED yield curves, bond duration, sector breakdowns, scenario rebalancing —...

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.7k

Updated

Oct 10, 2026

Version

4.10.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.7K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.7K downloadsadoption · observed Oct 10, 2026
Latest release: 4.10.0release · observed Jun 15, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17ftndh5bds1agrm1vrfj3rm584x3ed:investorclaw

Install using `clawhub skill install s17ftndh5bds1agrm1vrfj3rm584x3ed:investorclaw` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/perlowja/investorclaw before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-perlowja-investorclaw/snapshot"

Documentation

CLAWHUB

160,000 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

agent-skills/claude-code/SKILL.md

---
name: investorclaw
description: Deterministic-first portfolio analyzer for Claude Code via MCP-HTTP at localhost:18090. Holdings, performance, Sharpe + Sortino, FRED yields, bond duration, scenario rebalancing.
homepage: https://github.com/argonautsystems/InvestorClaw
user-invocable: true
metadata: {"license":"MIT-0","version":"4.7.7","runtime":"claude-code","image":"ghcr.io/argonautsystems/ic-engine:4.7.7-cpu","mcp-endpoint":"http://localhost:18090/mcp"}
---

<!--
SPDX-License-Identifier: MIT-0
Copyright 2026 InvestorClaw Contributors

This SKILL.md is MIT-0-licensed. It describes the Claude Code marketplace
plugin that connects to InvestorClaw v4.0 (Apache 2.0). The plugin
ships only this file, INSTALL.md, and a manifest — no Python, no bundle.
-->

# InvestorClaw — Claude Code Plugin (v4.0)

> Powered by [InvestorClaw](https://investorclaw.app) (Apache 2.0).
> This plugin is MIT-0-licensed.

## What this is

InvestorClaw is a containerized portfolio analysis service. The user
runs it locally as two Docker containers via `docker compose up -d`;
this Claude Code plugin is the thin client that registers the service's
MCP servers with your agent and exposes two convenience slash commands.

The plugin is a manifest + this SKILL.md + a one-time config write
that points Claude Code at two HTTP MCP endpoints on localhost. All
analysis happens inside the user's Docker containers — the agent
never installs or imports anything.

This is the current Claude Code / Claude Desktop path. The plugin
installs directly from this repo and uses the same skill bundle and
same container-first runtime as every other agent. See
`docs/GETTING_STARTED.md` for the canonical setup.

## Slash commands the plugin exposes

The plugin registers two slash commands so portfolio questions don't
depend on the LLM spontaneously deciding to call MCP tools:

- **`/ask <question>`** — routes to the `investorclaw.portfolio_ask`
tool. Pass the user's natural-language portfolio question (e.g.,
`/ask what are my top 5 dividend payers?`). The deterministic engine
picks the right analyzer and returns a structured `ic_result` plus
narrative text.

- **`/refresh`** — routes to `investorclaw.portfolio_refresh`. Pulls
fresh market data without re-uploading portfolio files. Use this when
the user has been chatting for a while and quotes may be stale.

These commands are deterministic entry points: the user types the slash
command, Claude Code dispatches it to the named MCP tool, the engine
returns structured output. **No LLM routing decision is involved at the
slash-command boundary.** This is by design — slash commands are
load-bearing for reliability.

## MCP tools available (after install)

When InvestorClaw is running and the plugin is loaded, your tool
catalog gains:

### Portfolio analysis (`investorclaw.*`)

- `investorclaw.portfolio_ask` — natural-language question router (also
invoked by `/ask`)
- `investorclaw.portfolio_refresh` — market-data refresh (also invoked

agent-skills/claude-desktop/SKILL.md

---
name: investorclaw
description: Deterministic-first portfolio analyzer for Claude Desktop via MCP-HTTP at localhost:18090. Holdings, performance, Sharpe + Sortino, FRED yields, bond duration, scenario rebalancing.
homepage: https://github.com/argonautsystems/InvestorClaw
user-invocable: true
metadata: {"license":"MIT-0","version":"4.7.7","runtime":"claude-desktop","image":"ghcr.io/argonautsystems/ic-engine:4.7.7-cpu","mcp-endpoint":"http://localhost:18090/mcp"}
---

<!--
SPDX-License-Identifier: MIT-0
Copyright 2026 InvestorClaw Contributors

This SKILL.md is MIT-0-licensed. The InvestorClaw service it connects to is
Apache 2.0. See ../../LICENSE-MIT-0 for the full MIT text.
-->

# InvestorClaw — Claude Desktop Reference

> Powered by [InvestorClaw](https://investorclaw.app) (Apache 2.0).
> This reference doc is MIT-0-licensed; the underlying service is Apache 2.0.

## What this is

[InvestorClaw](https://investorclaw.app) is a containerized, deterministic
portfolio analysis service. It runs on your machine as two Docker
containers (a Rust memory server and a Python analysis engine) and
exposes its capabilities to Claude Desktop over MCP-HTTP.

Claude Desktop has no plugin system — instead, it connects to MCP servers
declared in `claude_desktop_config.json`. Once you run
`docker compose up -d` and add two short blocks to that config file
(see `INSTALL.md`), Claude Desktop gains an entire portfolio-analysis
toolkit that you can invoke just by chatting.

There is no marketplace step. There is no plugin to install. The
service is the substrate; Claude Desktop is the interface.

## Tools that become available after install

Once both MCP servers are wired up and Claude Desktop has been fully
quit and relaunched, the model gains two new tool namespaces.

### Portfolio analysis (`investorclaw.*`)

| Tool | What it does |
|---|---|
| `investorclaw.portfolio_ask` | Natural-language question routed through the deterministic engine |
| `investorclaw.portfolio_holdings` | Current snapshot of positions, values, and weights |
| `investorclaw.portfolio_performance` | Sharpe, volatility, top/bottom performers, max drawdown |
| `investorclaw.portfolio_bonds` | Bond analytics — YTM, duration, FRED yield curve |
| `investorclaw.portfolio_analyst` | Analyst consensus ratings per holding |
| `investorclaw.portfolio_news` | News correlation for held positions |
| `investorclaw.portfolio_lookup` | Ticker / account lookup |
| `investorclaw.portfolio_optimize` | Modern Portfolio Theory (Sharpe / min-vol) |
| `investorclaw.portfolio_rebalance` | Current vs. target with tax impact |
| `investorclaw.portfolio_scenario` | What-if scenarios (rate moves, drawdowns) |
| `investorclaw.portfolio_cashflow` | Projected dividends and bond coupons |
| `investorclaw.portfolio_peer` | Peer comparison vs. benchmark |
| `investorclaw.portfolio_setup` | Auto-discover portfolio files in `/data/portfolios/` |
| `investorclaw.portfolio_refresh` | Refresh market data without re-uploading

agent-skills/hermes/SKILL.md

---
name: investorclaw
description: Deterministic-first portfolio analyzer for Hermes via MCP-HTTP at localhost:18090. Holdings, performance, Sharpe + Sortino, FRED yields, bond duration, scenario rebalancing.
homepage: https://github.com/argonautsystems/InvestorClaw
user-invocable: true
metadata: {"license":"MIT-0","version":"4.7.7","runtime":"hermes","image":"ghcr.io/argonautsystems/ic-engine:4.7.7-cpu","mcp-endpoint":"http://localhost:18090/mcp"}
---

<!--
SPDX-License-Identifier: MIT-0
Copyright 2026 InvestorClaw Contributors

This SKILL.md is MIT-0-licensed and tailored for the NousResearch Hermes
Agent (v0.12+). The InvestorClaw service it connects to is Apache 2.0.
See LICENSE-MIT-0 in this directory.
-->

# InvestorClaw — Hermes Skill (v4.0)

> Powered by [InvestorClaw](https://investorclaw.app) (Apache 2.0).
> This skill file is MIT-0-licensed; the underlying service is Apache 2.0.

## TL;DR for hermes operators

InvestorClaw v4.0 turns hermes into a **first-class portfolio-analysis
agent**. The service runs as two local Docker containers and exposes
its capabilities over MCP-HTTP. Hermes 0.12+ registers the MCP servers
as native function-callable tool sources — the LLM sees
`investorclaw.portfolio_ask`, `mnemos.search_memories`, and friends in
the same tool catalog as `browser_*`, `terminal`, and `skill_view`.

**Headline upgrade — HER-1 is gone.** Read the next section if you
remember v2.x.

## What changed since v2.x — HER-1 elimination

If you ran InvestorClaw v2.x against hermes, you hit **HER-1**: the
"skill-as-doc-hint" caveat. In v2.x, InvestorClaw shipped as a hermes
skill bundle injected into the system prompt. The LLM had to use
hermes meta-tools (`skill_view`, `terminal`) to *read* the skill
documentation and then *imitate* the analyst commands by shelling out.
That indirection layer was lossy and slow, and the Linux baseline
empirical reliability landed around **8% (2.3/30)** on the standard
prompt barrage — vs **77%** on zeroclaw, which had real tool
registration.

**v4.0 ends that.** There is no skill bundle to inject. The
deterministic engine runs as a containerized service and publishes its
analytical surface over MCP-HTTP. Hermes 0.12+ registers MCP servers
declaratively in `~/.hermes/config.yaml` and exposes their tools to
the LLM directly — same dispatch path as any other built-in tool.

What this means in practice for hermes users:

- **No more meta-tool indirection.** The LLM calls
`investorclaw.portfolio_ask` directly, not via `skill_view` →
`terminal` → fragile shell parsing.
- **Reliability now matches other agent runtimes.** Expect the same
routing accuracy as zeroclaw / openclaw — roughly an order of
magnitude better than v2.x on the same prompts.
- **Memory is built in.** The `mnemos.*` tool family gives hermes a
persistent memory layer it never had before, scoped to InvestorClaw
observations and user preferences.
- **No skill bundle to keep in sync.** Bumping the service to a newer
ic-engine ver

agent-skills/openclaw/SKILL.md

---
name: investorclaw
description: Deterministic-first portfolio analyzer for OpenClaw via MCP-HTTP at localhost:18090. Holdings, performance, Sharpe + Sortino, FRED yields, bond duration, scenario rebalancing.
homepage: https://github.com/argonautsystems/InvestorClaw
user-invocable: true
metadata: {"license":"MIT-0","version":"4.7.7","runtime":"openclaw","image":"ghcr.io/argonautsystems/ic-engine:4.7.7-cpu","mcp-endpoint":"http://localhost:18090/mcp"}
---

<!--
SPDX-License-Identifier: MIT-0
Copyright 2026 InvestorClaw Contributors

This SKILL.md is MIT-0-licensed. The InvestorClaw service it connects to
is Apache 2.0. See the InvestorClaw repository for that license.
-->

# InvestorClaw — Skill (openclaw runtime)

> Powered by [InvestorClaw](https://investorclaw.app) (Apache 2.0).
> This skill file is MIT-0-licensed; the underlying service is Apache 2.0.

## What this is

InvestorClaw is a containerized portfolio-analysis service exposed to
openclaw as **two MCP-HTTP servers**:

- `investorclaw` — portfolio analysis tools at `http://localhost:18090/mcp`
- `mnemos` — memory + knowledge graph at `http://localhost:5002/mcp`

Both run inside a Docker compose stack on the user's machine
(`docker compose up -d` is the entire service install). openclaw connects
to them as native MCP servers via its `mcp.servers` config block —
no plugin manifest, no `dist/index.js`, no npm install, no skill
bootstrap files.

If openclaw runs in a container itself, the two MCP URLs reach the host's
loopback through the compose bridge network or `host.docker.internal`,
depending on how the openclaw container is launched. See `INSTALL.md`.

## Tool surface

When the service is running, openclaw's tool catalog gains:

### Portfolio analysis (`investorclaw.*`)

- `investorclaw.portfolio_ask` — natural-language portfolio question
  routed through the deterministic engine
- `investorclaw.portfolio_holdings` — current snapshot of positions,
  values, weights
- `investorclaw.portfolio_performance` — Sharpe, volatility, top/bottom
  performers, max drawdown
- `investorclaw.portfolio_bonds` — bond analytics (YTM, duration, FRED
  yield curve)
- `investorclaw.portfolio_analyst` — analyst ratings per holding
- `investorclaw.portfolio_news` — news correlation for held positions
- `investorclaw.portfolio_lookup` — ticker / account lookup
- `investorclaw.portfolio_optimize` — Sharpe / min-vol optimization
- `investorclaw.portfolio_rebalance` — current vs target with tax impact
- `investorclaw.portfolio_scenario` — what-if scenarios on holdings
- `investorclaw.portfolio_cashflow` — projected cashflow from bonds
- `investorclaw.portfolio_peer` — peer comparison vs benchmark
- `investorclaw.portfolio_setup` — auto-discover portfolio files in
  `/data/portfolios/`
- `investorclaw.portfolio_refresh` — refresh market data without
  re-uploading files
- `investorclaw.portfolio_guardrails` — view educational-only guardrails

### Memory (`mnemos.*`)

- `mnemos.search_memories` — full-text +

agent-skills/zeroclaw/SKILL.md

---
name: investorclaw
description: Deterministic-first portfolio analyzer for ZeroClaw via MCP-HTTP at localhost:18090. Holdings, performance, Sharpe + Sortino, FRED yields, bond duration, scenario rebalancing.
homepage: https://github.com/argonautsystems/InvestorClaw
user-invocable: true
metadata: {"license":"MIT-0","version":"4.10.0","runtime":"zeroclaw","image":"ghcr.io/argonautsystems/ic-engine:4.10.0-cpu","mcp-endpoint":"http://localhost:18090/mcp"}
---

## Authoritative operating contract

These rules govern any agent using this skill. Examples elsewhere in this file
are reference only and never override them.

### Data integrity — InvestorClaw is the only source of truth
- Every price, percent, dollar figure, or market fact an agent states MUST come
from an InvestorClaw tool result returned in the SAME turn. InvestorClaw
returns HMAC-signed envelopes; that signed data is the only source of truth.
- Never invent, estimate, guess, or use the model's own training knowledge for
any number. If a tool did not return it this turn, do not state it — say
"InvestorClaw returned no data for that".
- Tool prose with no concrete numbers = no data; never convert it into a figure.

### Current tool surface (underscore namespace)
- `investorclaw__portfolio_market_snapshot(symbols?, benchmarks?)` — real-time
prices + day-change% for holdings and benchmarks (SPX/NDX/DJI/VIX, BTC/ETH).
`symbols` is a COMMA-SEPARATED STRING (e.g. "NVDA,AAPL"), not a list. No args =
holdings + benchmarks. Use this (not portfolio_ask) for any "price of X" and to
read the portfolio against the market.
- `investorclaw__portfolio_performance_window(period=...)` — return / P&L /
movers over a window. period: 1d, 1w, 1mo, 1y, 5y, 10y, 20y, max, or natural
phrases ("today", "last week", "last year", "entire history").
- `investorclaw__portfolio_ask(question=...)` — analysis / explanation.

Older `investorclaw.*` dot-namespace examples below are stale; the underscore
forms above are the current tool names.

## Autonomous / always-on monitoring agents

For unattended agents (scheduled monitors and alerters — e.g. a MarketWatch
agent), in addition to the contract above:
- Drive each run from a tool call first; never answer a market question from
memory. A scheduled "poll" means call `portfolio_market_snapshot`.
- Threshold scan: call `portfolio_market_snapshot`, then emit ONE terse line
only when a holding or benchmark breaches the configured move (e.g. ±3% a
holding, ±10% VIX); otherwise emit a single `NO_ALERT` token and stop.
- If the required tool errors or returns no data, emit a fixed marker such as
`OPS_FAIL market_snapshot unavailable` and stop — never fabricate a reassuring
number to fill the gap.
- No clarifying questions in unattended mode; map intent and act.
- Periodic / EOD reports: pull `portfolio_performance_window` for the window,
then `portfolio_market_snapshot` for index closes; report numbers verbatim.
- Always read holdings in the co

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