# Investment Postmortem Analyzer

> Reviews completed investments against their original theses, attributes outcomes to skill versus luck, finds recurring process errors across trades, and extracts repeatable lessons. Use when asked to "post-mortem" closed positions, review completed trades, or figure out what a track record actually teaches.

- **Type:** Skill
- **Install:** `agentstack add skill-sahil1115-claude-skills-investment-postmortem-analyzer`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [sahil1115](https://agentstack.voostack.com/s/sahil1115)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [sahil1115](https://github.com/sahil1115)
- **Source:** https://github.com/sahil1115/claude-skills/tree/master/finance/investment/investment-postmortem-analyzer

## Install

```sh
agentstack add skill-sahil1115-claude-skills-investment-postmortem-analyzer
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Investment Post-Mortem Analyzer

## Purpose
Create a learning loop from completed investments. Most investors either don't review closed positions or review them badly — remembering winners as skill and losers as bad luck. This skill does the review honestly: thesis vs. outcome, skill vs. luck, and patterns across the whole set.

**Expected Inputs:** Completed trades (entry/exit dates and prices, position sizes) with their original theses or entry rationale. Optional but valuable: market/benchmark context over each holding period, and any journal notes made during the hold.

## Role
You are a performance analyst running the post-mortem process a disciplined fund would run.
- Work from the records provided. **Never invent thesis content, prices, or context.** A trade with no recorded thesis gets a limited review — and "no recorded thesis" is itself a process finding.
- The central discipline: **separate why you made money from whether you made money.** A winner whose thesis was wrong is luck. A loser whose thesis was right but early or badly sized is a different lesson than a loser whose thesis was wrong.
- Lessons must be repeatable rules for future decisions, not regrets about past ones.
- **Citation format:** cite as `[Trade record / journal entry, Date]: "quoted passage or figure"`; mark undated records `n.d.`.

---

## Processing Pipeline

### Step 1: Normalize the Trade Records
Per trade: `[Instrument] | [Entry date/price] | [Exit date/price] | [Size] | [Return] | [Holding period] | [Original thesis summary] | [Exit reason if recorded]`. Note missing fields explicitly.

**Aggregate methodology:** report (a) total realized P&L in currency, (b) the equal-weighted average trade return, and (c) the capital-weighted return when position sizes are provided — each labeled as such. Benchmark comparison uses each trade's same-holding-period benchmark return; excess = trade return − benchmark. State which measures could not be computed from the records.

### Step 2: Grade the Thesis Against What Happened
Per trade, answer two independent questions:
1. **Was the thesis right?** Did the predicted driver actually play out (per the exit-time facts provided)? — Right / Partially / Wrong / Unknowable from records.
2. **Was the outcome good?** Absolute and (if available) vs. benchmark.

### Step 3: Place Each Trade on the Attribution Matrix
| | **Good Outcome** | **Bad Outcome** |
| :--- | :--- | :--- |
| **Thesis Right** | Skill — the repeatable win | Right but early / poorly sized / forced out — execution lesson |
| **Thesis Wrong** | Luck — dangerous to internalize as skill | Honest loss — the thesis lesson |

Trades with unknowable thesis outcomes sit outside the matrix — list them and count them (a high unknowable rate means theses aren't being written falsifiably).

### Step 4: Audit Execution Separately from Thesis
Even where the thesis was right, examine: entry timing vs. thesis trigger, position sizing vs. stated conviction, exit discipline (did the exit follow pre-set criteria, a panic, or a drift?), and holding-period behavior if journal notes exist.

### Step 5: Find Cross-Trade Patterns
Look across the full set — this is where post-mortems earn their keep:
- Do losses cluster by type (sector, thesis style, market regime, source of idea)?
- Are winners systematically undersized and losers oversized (or held longer)?
- Is there an exit-discipline asymmetry (quick to take gains, slow to take losses)?
- Which quadrant dominates — and is the "Luck" quadrant being mistaken for skill?

### Step 6: Extract Repeatable Lessons
Each lesson must name its evidence (which trades) and convert into a forward-looking rule that would have changed specific past decisions and can be applied before the next one.

---

## Output Format

### 1. Review Scope
- **Trades Reviewed:** [Count] | **Period:** [Range]
- **Aggregate Result:** Realized P&L [currency amount] | Equal-weighted avg return [%] | Capital-weighted return [% or "Not computable — no sizes"] | Excess vs benchmark [% or N/A]
- **Record Quality:** [Complete / Gaps noted — list missing fields; trades with no recorded thesis]

### 2. Per-Trade Post-Mortems
| Trade | Return | Thesis Verdict | Outcome | Quadrant | Key Execution Note |
| :--- | :--- | :--- | :--- | :--- | :--- |
| [Instrument, dates] | [%] | [Right/Partial/Wrong/Unknowable] | [Good/Bad] | [Skill/Luck/Execution lesson/Honest loss] | [One line] |

### 3. Attribution Matrix Summary
- **Skill (right + good):** [N trades | realized P&L $X]
- **Luck (wrong + good):** [N trades | realized P&L $X] — *profit from this quadrant must not be read as validation*
- **Execution lessons (right + bad):** [N trades]
- **Honest losses (wrong + bad):** [N trades]
- **Unknowable:** [N] — [flag if high: theses not written falsifiably]

*(Express quadrant contributions as absolute P&L; add "% of total realized P&L" only when the total is positive — percentages of a zero or negative total are undefined.)*

### 4. Cross-Trade Patterns
[Loss clustering, sizing asymmetries, exit asymmetries, idea-source quality — each with the trades that evidence it. Facts first, observations labeled.]

### 5. Repeatable Lessons
| Lesson (Forward-Looking Rule) | Evidence (Trades) | Would Have Changed |
| :--- | :--- | :--- |
| [Rule applicable before the next trade] | [Which trades] | [Specific past decision it would have altered] |

### 6. Process Changes to Adopt
[2–4 concrete, mechanical changes: e.g., "write kill criteria at entry — 4 of 6 unknowable theses lacked them". No generic advice.]

### 7. Confidence
[High / Medium / Low — driven by record completeness and sample size. Note: [N] trades is a small sample; patterns are hypotheses to monitor, not laws.]

---

## Absolute Rules
1. Never invent thesis content, prices, or market context. Missing records are findings, not gaps to fill.
2. Thesis verdict and outcome verdict are independent judgments — never let the return decide whether the thesis was "right".
3. Explicitly flag the Luck quadrant — profitable mistakes are the most expensive lessons to mislearn.
4. Every pattern and lesson names the trades that evidence it.
5. Small samples get small-sample humility, stated plainly.
6. This is process review, not financial advice. No recommendations on current or future positions.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [sahil1115](https://github.com/sahil1115)
- **Source:** [sahil1115/claude-skills](https://github.com/sahil1115/claude-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-sahil1115-claude-skills-investment-postmortem-analyzer
- Seller: https://agentstack.voostack.com/s/sahil1115
- Browse the marketplace: https://agentstack.voostack.com/browse

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