Producing a software estimate that carries its own uncertainty instead of hiding it: a range with explicit probability assumptions when supported, decomposition, PERT and the limits of summing task estimates, calibrating against what this team has actually done, and keeping estimate, target and commitment as three separate things. Use when asked how long something will take, when a single date is being requested for work that has not been broken down, when an estimate is being treated as a pr...
Scanned 9/19/2026
Install to Claude Code
npx -y skills add robsonkades/agent-skills --skill estimation-under-uncertainty --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Estimation Under Uncertainty?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/robsonkades-estimation-under-uncertainty)More formats (shields.io, HTML) on the badges page.
---
name: estimation-under-uncertainty
description: >
Producing a software estimate that carries its own uncertainty instead of hiding it: a range
with explicit probability assumptions when supported, decomposition, PERT and the limits
of summing task estimates, calibrating against what
this team has actually done, and keeping estimate, target and commitment as three separate
things. Use when asked how long something will take, when a single date is being requested
for work that has not been broken down, when an estimate is being treated as a promise, when
padding is being added silently, when a plan is slipping and the message has not gone out
yet, or when someone asks for a number before the requirement is clear. Does not cover
clarifying the requirement itself (requirements-and-acceptance), how to deliver bad news
(engineering-communication), or trading quality for time (technical-debt-decisions).
---
# Estimation Under Uncertainty
## Purpose
An estimate predicts work or completion under assumptions. A single number without its
uncertainty can be planned against as certainty. Even a numerical range can mislead when
its coverage, scope or calendar assumptions are invented.
The job is to support the planning decision with a forecast and its uncertainty when evidence
permits, or identify what must be learned before a number is useful.
## Workflow
1. **Identify the decision and forecast event.** Reuse supplied scope, history and constraints;
ask only for missing information that changes the decision (requirements-and-acceptance).
Give a conditional range only when its bounds have a basis; pressure for a number does not
supply one. Otherwise state what prevents forecasting and the next useful investigation.
Define effort versus elapsed time, working versus calendar days, forecast date, start point,
total versus remaining work, completion criteria, capacity and dependencies.
2. **Decompose where it exposes omitted work or a material dependency.** Comparable whole-change
history may already be sufficient. Stop when more detail would not change the decision;
unfamiliar work needs explicit assumptions or investigation, not endless subdivision.
3. **Choose inputs supported by evidence**: comparable cycle-time samples or elicited
quantiles with explicit assumptions. If using PERT, distinguish bounds and modal inputs
from P10/P50/P90; they are not interchangeable. Without calibration, label the range
provisional and do not fabricate a coverage percentage
(`references/methods.md`).
4. **Combine them with their dependencies.** For a sum, expected values add; variances add
when covariances are zero, as under independence. Shared people, platforms, approvals and integration risks create
correlation; model them explicitly. Simulation does not infer missing dependencies or
capacity constraints. A sum of effort is not automatically elapsed project duration.
5. **Calibrate against comparable history.** Record sample count, start/end definitions,
changed team conditions and omissions. Three examples can anchor discussion, not establish
reliable tail percentiles. Compare forecasts with later outcomes without replacing old estimates.
6. **State the forecast event and assumptions**: a central P10–P90 interval has nominal 80%
coverage, while "by P80" is a model completion percentile, not an interval.
Discrete durations/rounding can change coverage; calibration requires actual outcomes.
Both require a stated model/basis. Otherwise report an uncalibrated scenario range.
7. **Re-estimate when evidence arrives**, and say so immediately. An estimate is a statement
about what you knew when you made it. Update when new evidence changes the decision or
risk materially; retain the original forecast and explain the change.
Deliver scope and completion criteria, estimate units/range and its basis, key assumptions,
target versus commitment if supplied, and the next evidence/re-estimation trigger. Scale
detail to the decision; do not invent a date, owner or probability merely to fill this shape.
## Rules
- Avoid a bare single number when uncertainty affects the decision. If supported, give the
range and explain the planning value selected from it for the decision's risk tolerance.
Keep assumptions and residual risks visible; an unsupported broad range is still a guess.
- State whether the range is a scenario span or a calibrated prediction interval, and whether
a quoted percentile is a deadline or interval endpoint. A confidence interval for a mean
does not describe the uncertainty of one future delivery.
- Estimate, target and commitment are three different things and must be named separately. An
estimate is what you predict, a target is what someone wants, a commitment is what you have
promised. Deriving an estimate from a target is how a project becomes late on day one.
- Do not pad silently. Hidden padding obscures assumptions and calibration. Put contingency
where it can be managed: at the plan level, visible, owned.
- The estimate covers the whole change, not the coding: tests, review, the review round trip,
migration, deployment and anticipated rework. Avoid counting these twice if historical
elapsed-time samples already include them.
- Name the uncertainty an investigation could resolve and its timebox. A spike can reveal
more work and widen a range; do not promise a specific reduction without evidence.
- Report a slip when you believe it, not when it becomes undeniable. The information is worth
most while there is still time to change something; overdue updates still matter for
downstream plans (engineering-communication).
- Never resolve a schedule problem by silently lowering quality. If something must give, name
it and let the trade be decided (technical-debt-decisions).
## References
- **Methods and arithmetic** — `references/methods.md`. Three-point estimation and PERT with
worked numbers, when variances add, decomposition, reference-class
forecasting from your own history, the cone of uncertainty, and the failure modes of each
method. Read when selecting a method, combining work, forecasting remaining time or checking calibration.
- **Estimates, targets and commitments** — `references/commitments.md`. Keeping the three
apart, what to do when a target is presented as an estimate, negotiating scope rather than
dates, communicating a slip, and the agent-specific version of the same discipline. Read when
an estimate is about to become a promise, or a plan is slipping.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!