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position-investigation

Investigate a position using portfolio context, exposure changes, market context, and approved research/data sources.

Skill by PM AI <pm-ai@example.com>

IndexedMIT
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/navoditk-position-investigation

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Investigate a position using portfolio context, exposure changes, market context, and approved research/data sources.

Use cases: data, research

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/position-investigation

What's inside

Skill name
position-investigation
Description
Investigate a position using portfolio context, exposure changes, market context, and approved research/data sources.
License
MIT
Metadata
author: PM AI <pm-ai@example.com>
Instructions
53 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (8)

  • CHANGELOG.md
  • SKILL.md
  • EVAL.md · evals/
  • config.yml · evals/
  • evals.json · evals/
  • grader.py · evals/
  • skill.yaml
  • README.md · tests/

SKILL.md (first lines)

# Position Investigation

## Use when

Use this skill when the user request clearly requires the capability described above.

## Do not use when

Do not activate this skill for unrelated market lookup, general education, or requests that can be answered without this business capability.

## Procedure

1. Resolve portfolio, scope, and relevant as-of date(s).
2. Call approved logical capabilities from the Agentic Data Pipeline.
3. Validate returned dates, identifiers, and coverage.
4. Reconcile quantitative claims whenever authoritative totals exist.
5. Identify material results rather than narrating every field.
6. Explain uncertainty or missing data explicitly.
7. Produce a concise PM-oriented answer grounded in tool results.

## Data and tool rules

- Prefer authoritative internal analytical capabilities over independent LLM calculations.
- Never fabricate a portfolio value, benchmark, position, return, exposure, or risk statistic.
- Never bypass authorization.
- Preserve source and as-of metadata for quantitative claims.
- In the sandboxed reference evaluation, invoke the staged deterministic bridge
  with `python /workspace/repo/synthetic_data_pipeline/tool_cli.py TOOL_NAME`
  and the relevant flags. Treat its JSON response as the logical-tool result.

## Domain rules

- Use `portfolio.positions` for the position's weight and portfolio context,
  and `market.security_context` for security-level facts; do not blend the
  two into a single unlabeled claim.
- Investigate exactly the position named in the request; do not substitute
  a different position with a similar name or sector.
- Never infer a missing security fact or research context; report it as
  unavailable instead.

## Output

Provide:
- key conclusion;
- material drivers;
- supporting quantitative evidence;
- important limitations/data gaps.

For traceability, end the response with `Workflow: position-investigation`
after completing the workflow. This marker is an execution trace, not a
substitute for the supporting evidence.

From navoditk/pm-ai-skills-framework, MIT.

More from navoditk/pm-ai-skills-framework

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Last commit (this folder)
Sep 1, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

position-investigation skill. Agent Mart. https://agentmart.dev/skills/navoditk-position-investigation (last updated 2026-10-24)