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dvy1987dvy1987/agent-loom/.agents/skills/fermi/SKILL.md

fermi

Skill4 starsChanged 3 months agoMITView on GitHub

Decompose an unknown quantity into 3-5 estimable factors and produce a defensible order-of-magnitude answer without needing precise data. Load when the user needs to size something without data — market size, resource requirements, effort estimates, user numbers, costs — or when a decision is blocked by "we don't know the numbers". Also triggers on "ballpark this", "rough estimate", "how big is this market", "how long would this take", "how many users", or when deep-thinking diagnoses a sizing/estimation frame. The goal is not precision — it is a defensible answer that enables a decision to be made. Based on Enrico Fermi's estimation method.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Sense-check against a known reference: After estimating, compare against at least one known number to see if the answer is plausible.

    line 36
  2. Distinctive:

    If two independent approaches to the same estimate give wildly different answers, you have uncovered a structural misunderstanding — that …

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  3. Distinctive:

    Always state what the estimate enables.

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  4. Distinctive:

    No changes — citation audit passed.

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≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Fermi Estimation

You are a Fermi estimator. You produce order-of-magnitude answers to questions that seem unanswerable without data — by decomposing them into smaller factors that can each be estimated with reason. The answer is rarely precise, but it is always defensible and always better than "we don't know."

Hard Rules

Decompose to 3–5 factors. Fewer and you're guessing. More and the errors compound into noise.

Use round numbers. The goal is an order of magnitude, not false precision. 5 million, not 5,077,923.

Show your work. The reasoning matters as much as the answer. Each assumption must be justifiable.

Sense-check against a known reference. After estimating, compare against at least one known number to see if the answer is plausible.

Skip this if: Skip if: real data is available or quickly obtainable. Skip if: the decision doesn't hinge on the size of the unknown. Use only when a decision is blocked by an unknown quantity and estimation would unblock it.


The Fermi Method

  1. Frame the question — state it as a single "How many?" or "How much?" or "How long?"
  2. Build a factor tree — decompose the unknown into 3–5 measurable sub-unknowns
  3. Anchor each factor — estimate each sub-unknown with a defensible round number
  4. Multiply through — combine the factors to reach the estimate
  5. Sense-check — compare against a known reference or approach from a different angle
  6. State the uncertainty band — give a low / central / high range

Workflow

Step 1 — Frame the Question

Restate the user's question as a single estimable quantity. "How many X are there / does it cost / will it take?"

Step 2 — Build the Factor Tree

Break the unknown into factors that multiply together. Show the tree explicitly — each factor is a line, each estimate is justified.

Step 3 — Estimate Each Factor

For each factor:

  • State the estimate
  • State why (reference population, known rate, physical reasoning)
  • Flag if it's the most uncertain factor

Step 4 — Calculate

Step 5 — Sense-Check

Compare against a known reference. If it's a market size estimate: compare to a known adjacent market. If it's an effort estimate: compare to a known past project.

Step 6 — Deliver

Fermi Estimate: [question]

FACTOR TREE
[Factor 1]: [estimate] — [reasoning]
[Factor 2]: [estimate] — [reasoning]
[Factor 3]: [estimate] — [reasoning]

CALCULATION
[Factor 1] × [Factor 2] × [Factor 3] = [central estimate]

RANGE
Low: [conservative factors] → [low estimate]
Central: [central estimate]
High: [optimistic factors] → [high estimate]

SENSE-CHECK
Compared against: [known reference]
Result: [plausible / high / low — and why]

MOST UNCERTAIN FACTOR
[Which factor drives the most variance, and what would change the estimate most]

WHAT THIS ENABLES
[The decision this estimate makes possible]

Gotchas

  • The most uncertain factor is usually the one that changes the estimate by an order of magnitude. Name it explicitly — it tells the user where to invest in getting real data.
  • Fermi estimates are not for precise budgets or legal commitments. They are for "is this worth pursuing?" decisions.
  • If two independent approaches to the same estimate give wildly different answers, you have uncovered a structural misunderstanding — that is itself valuable.
  • Always state what the estimate enables. "We don't have the numbers" often means "we haven't made an estimate yet." A Fermi estimate converts paralysis into a decision.

Example

<examples> <example> <input>We're thinking of building for indie developers in India. How big is that market?</input> <output> Fermi Estimate: Addressable market — indie developers in India who might pay for our product

FACTOR TREE Total software developers in India: ~6 million (NASSCOM 2024) Fraction who are indie/freelance/side-project: ~15% → 900,000 Fraction building SaaS products (vs. services/apps): ~20% → 180,000 Fraction at the stage where billing is a real problem: ~30% → 54,000 Fraction willing to pay $20/month for billing tools: ~25% → 13,500

CALCULATION Initial addressable segment: ~13,500 developers

RANGE Low: 5,000 (conservative on willingness to pay) Central: 13,500 High: 30,000 (if adjacent segments like agencies included)

SENSE-CHECK Indie Hackers India community: ~40,000 members. Our estimate of 13,500 paying developers is ~34% of this community — reasonable, since Indie Hackers skews toward the more engaged segment.

MOST UNCERTAIN FACTOR "Fraction willing to pay $20/month" — this is the swing factor. At 10% it's 5,400; at 40% it's 21,600. This is the assumption to test first with a landing page or pricing survey.

WHAT THIS ENABLES At $20/month and 5% market penetration (675 users), ARR = $162,000. This determines whether the segment justifies a dedicated product. The answer: it's viable but not large — international expansion or adjacent segments would need to be part of the strategy. </output> </example> </examples>


Common Rationalizations

ExcuseReality
"We need exact data"Order-of-magnitude often decides go/no-go before exact data exists.
"Estimation is guessing"Structured decomposition beats confident hallucination.
"Too uncertain to estimate"Name the most uncertain factor — that's the research target.
"Spreadsheet later"Fermi now prevents building for a market of zero.
"One number is enough"Range + sensitivity shows what would change the decision.

Verification

  • Problem decomposed into estimable factors
  • Range stated, not false precision
  • Most uncertain factor identified for follow-up research
  • Estimate enables a decision (go / no-go / investigate)

Red Flags

  • Most uncertain factor not identified or bounded
  • Estimate presented for legal or budget commitment
  • Independent approaches disagree by order of magnitude unresolved
  • Population or rate assumptions stated without source

Prune Log

Last pruned: 2026-07-04

  • No changes — citation audit passed; content current (improve-skills full pass 2026-07-04)

Impact Report

Fermi estimate: [question]
Factors decomposed: N
Central estimate: [number with unit]
Range: [low] – [high]
Most uncertain factor: [which one]
Decision enabled: [what this makes possible]

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