Estimation Stinger

---
name: "estimation-stinger"
license: AGPL-3.0-or-later
description: "Forecast software delivery. Use for relative sizing, NoEstimates, cycle-time data, or Monte Carlo forecasts. Read README.md for the guide map."
---

# Estimation Stinger

Procedural arsenal for `estimation-wasp-drone`, the Wasp Nest's authority on software estimation and probabilistic delivery forecasting.

This stinger encodes:

- The canonical relative-sizing frameworks: Fibonacci story points, T-shirt sizing, Planning Poker, and when each applies.
- The NoEstimates movement: Vasco Duarte's throughput-as-forecast argument, prerequisites, and the honest evidence gap (no controlled RCTs).
- The planning-fallacy literature: why expert estimators are systematically wrong, the inside-view / outside-view distinction, and Kahneman/Tversky/Flyvbjerg's recommended remedy (reference class forecasting).
- Monte Carlo simulation: how it works, what data it needs, the 2026 free tooling landscape, and practical setup for teams with cycle-time history.
- The five-category dysfunction diagnosis that tells you WHICH technique to recommend before you recommend anything.

It does NOT encode sprint planning ritual design, Jira/Linear configuration, team capacity planning formulas, or vendor procurement.

## When this stinger applies

Load when `estimation-wasp-drone` is invoked. Typical user phrases:

- "Our velocity is meaningless / our story points drift every sprint"
- "Should we adopt NoEstimates?"
- "How do we T-shirt size our roadmap?"
- "We need a date with a confidence level for Q3"
- "Why do our estimates always come out wrong?"
- "Monte Carlo for delivery forecasting: explain it to my PM"
- "Our team says 2 weeks, it always takes 6"

Do NOT load for:

- Sprint ceremony design (retrospectives, planning, refinement): agile coaching domain
- Jira/Linear/Azure DevOps configuration: tooling domain
- Velocity tracking or charting: project management tooling domain

## First action when this stinger is loaded

Read these three files before doing anything:

1. **`guides/00-principles.md`**: the estimation-vs-forecasting distinction, the commitment trap, and the single most important framing: estimates are a communication tool, not a planning oracle.
2. **`guides/01-diagnosis.md`**: the five dysfunction categories. Always diagnose before recommending; the wrong framework for the wrong dysfunction makes things worse.
3. **`research/research-summary.md`**: the research manifest; tells you which external files cover which topics so you can fetch evidence when you need it.

Then read the specific guide for the technique the team needs.

## Folder layout

```text
estimation-stinger/
+- SKILL.md                     (this file — master index)
+- README.md                    (one-page human overview)
+- guides/
|  +- 00-principles.md          (estimation vs. forecasting; the commitment trap; scope and handoffs)
|  +- 01-diagnosis.md           (five dysfunction categories; decision tree for technique selection)
|  +- 02-relative-sizing.md     (Fibonacci story points, T-shirt sizing, Planning Poker)
|  +- 03-noestimates.md         (NoEstimates movement; prerequisites; throughput substitution; evidence base)
|  +- 04-monte-carlo.md         (Monte Carlo simulation; inputs; confidence percentiles; 2026 tooling)
|  +- 05-planning-fallacy.md    (planning fallacy; optimism bias; inside vs. outside view; remedies)
+- examples/
|  +- fibonacci-estimation-session.md  (worked estimation session from backlog → sized stories)
|  +- monte-carlo-forecast.md          (worked 40-item backlog forecast with P50/P85/P95 output)
+- templates/
|  +- estimation-advisory.md    (the output shape: diagnosis + recommendation + implementation steps)
+- reports/
|  +- README.md                 (advisory reports accumulate here over time)
+- research/                    (owned by scripture-historian — do NOT modify)
   +- research-plan.md
   +- research-summary.md
   +- index.md
   +- external/
      +- 01-noestimates.md
      +- 02-story-points-fibonacci.md
      +- 03-monte-carlo-forecasting.md
      +- 04-planning-fallacy.md
      +- 05-t-shirt-sizing.md
      +- 06-ai-estimation-and-tooling.md
```

## Critical directives (from Command Brief)

- **Never frame estimates as commitments without explicit stakeholder negotiation.** Why: the commitment trap is the primary driver of estimate-driven burnout.
- **Always distinguish relative sizing from probabilistic forecasting.** Why: story points answer "how big is this relative to that?"; they are not date predictors.
- **When recommending NoEstimates, always state the prerequisite: reliable cycle-time history.** Why: NoEstimates without data is not a methodology, it is an absence of information.
- **Cite the planning-fallacy literature when explaining why estimates are wrong.** Why: teams that understand the cognitive root cause accept data-driven alternatives; teams that think they need better estimators repeat the cycle.
- **Escalate velocity-configuration and sprint-ceremony questions.** Why: Jira/Linear setup and sprint ritual design are outside this Drone's domain.

## The evidence that matters (from research)

Key data points for advisory conversations:

- Replacing all story point values with "1" changes the forecast by only 8% (Maria Chec, 2025 Vasco Duarte interview). See `research/external/01-noestimates.md`.
- Only ~30% of software projects complete on time and on budget (Standish CHAOS). See `research/external/04-planning-fallacy.md`.
- IT projects average 27% cost overrun; 1 in 6 exceed 200% overrun (Flyvbjerg). See `research/external/04-planning-fallacy.md`.
- Initial software estimates are typically off by 2x-4x (McConnell). See `research/external/04-planning-fallacy.md`.
- Monte Carlo accuracy is 85-95% when based on quality historical data (montecarloestimation.com). See `research/external/03-monte-carlo-forecasting.md`.

---

*Command Brief: [`ai-tools/command-briefs/estimation-wasp-drone-command-brief.md`](../../command-briefs/estimation-wasp-drone-command-brief.md)*
*Part of The Wasp Nest, curated by [Mario Aldayuz a.k.a @thenotoriousllama](https://github.com/thenotoriousllama).*