What is the Trade Study Report skill?
Trade Study Report is a coding skill by Anthropic for Claude Code, Cursor, Codex and other AI coding agents. Turns a filled-in trade study matrix and its analysis results into a scored comparison and a decision memo, with every score cited to its source. Runs the sensitivity analysis every time — where the winner flips, which criterion the decision actually rests on, whether an option never wins under any plausible weighting — because a recommendation with no sensitivity check is a spreadsheet, not a decision.
A trade study is the formal way an engineering team chooses between design options: criteria that matter, weights on how much, options scored against each one, a weighted total that ranks them, and a memo that defends the pick in review.
What the SKILL.md covers
- Inputs
- Workflow
- Step 1 — Load the matrix
- Step 2 — Ingest analysis results
- Step 3 — Compute weighted totals and rank
- Step 4 — Run the sensitivity analysis
- Step 5 — Check constraint compliance, separately from scoring
- Step 6 — Write the decision memo
- Step 7 — Produce the scored comparison table
- Approval gates
- Author
- Anthropic
- Pack
- anthropics/claude-plugins-official (53 skills)
- Category
- Coding, #266 of 1763
- Alyn Score
- 79 / 99
- Files
- 4, includes references
- License
- Apache-2.0
- Last updated
- 13 h ago
- Works with
- Claude Code, Claude, Cursor, Codex, Gemini CLI, Copilot
Trade Study Report compared to similar skills
| Skill | Alyn Score | GitHub stars | Updated |
|---|---|---|---|
| Trade Study Report · Anthropic | 79 | 47k | 13 h ago |
| Competitive Matrix · alirezarezvani | 63 | 30k | 2 days ago |
| Decision Heuristics · kangarooking | 66 | 13k | 44 days ago |
| Gongwen Party · duyunzhoudyz | 60 | 809 | 33 h ago |
Install Trade Study Report
Pick your agent. Every command is ready to paste.
npx alyn-cli add trade-study-reportDetects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.
npx skills add anthropics/claude-plugins-official --skill trade-study-reportOr use the open skills CLI directly.
01
Install it
Run the command above, or upload the folder in Claude.
02
Ask naturally
Describe the task. Your agent loads trade-study-report when the request matches its description.
03
Name it if needed
If it does not trigger, say “use the trade-study-report skill”. In Codex, type $trade-study-report.
Trade Study Report
A trade study is the formal way an engineering team chooses between design options: criteria that matter, weights on how much, options scored against each one, a weighted total that ranks them, and a memo that defends the pick in review.
The analysis is the expert work; the memo is assembly. An engineer runs the simulations, then loses a day or more turning results into a document — assembling scores, writing up the reasoning, formatting a table, defending it the first time someone asks "what if cost mattered more?" This skill does the assembly.
It does not run analysis. It reads scores that already exist — from
design-space-explore's variant manifest, from a simulation report, from
engineering judgment stated plainly as judgment — and turns them into a
ranked, defensible comparison.
Quick start
→ Load the matrix: criteria, weights, options, scores. Weights sum to 100?
→ Every option scored against every criterion? Report the gap, never impute
→ Compute weighted totals and rank
→ Run the sensitivity analysis. Always — never optional
→ Check constraint compliance separately. A violation disqualifies, never
just lowers a score
→ Write the memo: recommendation, reasoning, what was ruled out, risks
→ Produce the scored comparison table, reviewable
Inputs
First, find the plant setup: from the task's own folder (never cd into the plugin), run
python3 -I <this skill's folder>/../../shared/scripts/plant_setup.py find, do its setup_page_first step, then read the profile at
profile_path and any rate at rates_path, per ../../shared/replies.md.
| Input | Source | Form |
|---|---|---|
| Trade study matrix — criteria, weights, options | M365 (Excel/Word), or defined in conversation | XLSX / DOCX / conversation |
| Analysis results per option | M365 (simulation reports, test data, spreadsheets) | Documents / CSV |
| Variant manifest | design-space-explore output |
../../shared/contracts/variant-manifest.md |
| Requirements and constraints | M365 requirements document | Documents |
| The plant's trade study memo template | ## Plant context, captured during onboarding |
Template |
| Prior trade studies | M365 | Documents — for format and precedent |
| Cost data per option | ERP cost: NetSuite standard cost, or Infor M3 last purchase price (../../shared/erp-connectors.md); or estimates |
Connector / documents |
Workflow
Step 1 — Load the matrix
Criteria, weights, options, scores. Validate that weights sum to 100, and that every option is scored against every criterion.
Report gaps rather than imputing a score. An unscored cell is a
finding, not a zero — filling it in with a guess is exactly the failure
this step exists to prevent. Read reference/matrix-and-scoring.md.
When the options come from a design-space-explore manifest, three
manifest-level signals surface here, before any scoring happens — per
../../shared/contracts/variant-manifest.md:
- A variant with
status: regeneration_failedorstatus: skippedis listed as an unevaluated option, excluded from the ranking, and stated as excluded — never scored, never silently dropped from the list. - A non-empty
requested_not_drivingmeans part of the requested design space was never explored. Say so. variant_count_confirmed: falsemeans the variant set itself was never confirmed with the engineer before generation. Note that in the report.
Step 2 — Ingest analysis results
Map each result to its criterion and option, citing the source document for every score.
Where the source is design-space-explore's variant manifest, read scores
from each variant's properties and analysis_results — never re-derive a
number the manifest already computed, and never re-run an analysis this
skill doesn't perform.
Step 3 — Compute weighted totals and rank
Score × weight, summed, per option.
Criterion direction must be explicit and verified before this step
runs. Some criteria are lower-is-better — mass, cost — and some are
higher-is-better. Getting one backward silently inverts the result, and
nothing about the arithmetic will look wrong when it happens. Read
reference/matrix-and-scoring.md.
Step 4 — Run the sensitivity analysis
Always. Never optional. Vary the weights across a plausible range and report where the winner flips, which criterion the decision actually rests on, and which options win under which weighting regimes.
This is the most valuable part of the skill and the part most often
skipped. Weights are subjective — somebody decided cost was 30% and
weight was 25% — and a recommendation with no sensitivity check hides
exactly how much that decision mattered. Read
reference/sensitivity-analysis.md.
Step 5 — Check constraint compliance, separately from scoring
An option that violates a hard requirement is disqualified, not low-scoring. These are different things, mixing them is a common error, and this skill keeps them apart throughout — a disqualified option never appears in the ranked comparison, only in its own list with the violated requirement named.
Step 6 — Write the decision memo
Recommendation, reasoning, the sensitivity finding, what was ruled out and
why, and the residual risks in the recommended option. Read
reference/decision-memo.md.
In the plant's own memo template where one was captured at onboarding.
A trade study goes into the design record and gets defended in a review, so it
has to arrive in the shape that record expects. Fall back to prior trade
studies for format, then to a neutral structure — and name which was used, so
nobody mistakes the house shape for their own.
Step 7 — Produce the scored comparison table
In a reviewable format, per Output below.
Approval gates
This skill recommends; it does not decide. The memo is a draft an
engineer reviews, signs, and defends in the design review — nothing here
commits the plant to a design choice, the same way customer-inquiry-intake
recommends a bid and root-cause-capa ranks candidate causes without
concluding.
Nothing is written back to any system of record.
Output
Every document this skill produces is printed in the reply, in full.
Saving a copy to a file as well is fine, as Word or Excel per ../../shared/replies.md, never .txt; a file instead of the reply is not.
The person reads the reply, and every delimited block and outbound check lives
in it — a document only on disk has been neither seen nor checked.
A record handed to another skill is saved and summarised, never pasted as
raw YAML; memory blocks are written where the plant's memory lives; and the
name on an approval is asked, never taken from the account. All three per
../../shared/replies.md.
The scored comparison table — options × criteria, weighted, ranked, with every score cited to its source. Each cell shows its contribution (normalized score × weight) beside the raw score, so a reader can see where a total came from without a calculator, and the table carries an explicit rank column rather than leaving the order to be inferred from the totals.
The sensitivity analysis — flip points, the most decision-sensitive criterion, and the regime-by-regime winners.
The decision memo — recommendation, reasoning, the sensitivity finding, ruled-out options with their cause, and the residual risks in the recommended option.
The constraint compliance summary — disqualified options listed separately from the ranked ones, each with the requirement it violated.
The memo is a controlled document: it follows the plant's own trade study
template, per ../../shared/artifact-style.md, and is never restyled. Where
no template is on file, use a plain neutral format and say the template is
missing. Only a separate internal comparison view, which the team refers back
to in review, uses the house artifact style.
Edge cases and failure modes
- Weights don't sum to 100 — report it. Do not normalize silently.
- An option is unscored on a criterion — report the gap. Never impute a score.
- Two options are within noise of each other — say so explicitly rather than presenting a false winner.
- Scores are on inconsistent scales — 1–5 against 1–10 against raw units. Normalize, and show the normalization.
- Some criteria are lower-is-better, some higher-is-better — direction must be explicit per criterion. Getting it wrong silently inverts the result.
- No analysis results yet, only the matrix — produce the scored comparison and clearly mark it as judgment-based, not analysis-based.
Degradation
Runs entirely from a filled-in matrix and pasted figures, with no connector and no CAD backend at all.
| Not available | What happens |
|---|---|
A variant manifest from design-space-explore |
The matrix and its options come from a document or conversation instead. A hand-authored manifest with cad_backend: none is a valid, complete input, not a fallback — per ../../shared/contracts/variant-manifest.md |
| Analysis results, on every option | The comparison runs on judgment alone and says so, throughout — every score reads as judgment-based, never presented as analysis-based |
| Analysis results, on some options | Score what is analyzed, report the gap per unanalyzed option, and never impute a score to fill it in |
| ERP cost | Price from a supplied estimate or a document, with its source, rather than leaving cost unscored |
| The plant's memo template | Fall back to prior trade studies for format; failing that, a neutral memo structure — and say which, because onboarding's gaps list promises exactly this degradation |
| Prior trade studies | Use a neutral memo structure and say the plant's own format was not available |
Chain position
Not part of a named chain. Consumes from design-space-explore
directly — the same producer-consumer relationship breakdown-diagnosis
has with daily-production-report in Chain 4.
Metric. Design decisions per quarter; design cycle time.
Reference files
| File | Load when |
|---|---|
reference/matrix-and-scoring.md |
Steps 1 to 3 — validating the matrix, citing scores, normalization, criterion direction |
reference/sensitivity-analysis.md |
Step 4 — always, before ranking is presented as final |
reference/decision-memo.md |
Steps 5 to 7 — constraint compliance, the memo, the comparison table |
../../shared/contracts/variant-manifest.md |
Step 2 — reading scores from a generated or hand-authored manifest |
Tips for Trade Study Report
- • Start a fresh session after installing so your agent picks up the new skill.
- • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
- • It is part of a pack with 53 skills. Install only the ones you need with --skill to keep triggers precise.
- • If two skills overlap, mention the one you want by name.
Questions about Trade Study Report
What does the Trade Study Report skill do?
Turns a filled-in trade study matrix and its analysis results into a scored comparison and a decision memo, with every score cited to its source. Runs the sensitivity analysis every time — where the winner flips, which criterion the decision actually rests on, whether an option never wins under any plausible weighting — because a recommendation with no sensitivity check is a spreadsheet, not a decision.
How do I install Trade Study Report?
Run "npx alyn-cli add trade-study-report" in your project. The Alyn CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.
Does Trade Study Report work in Cursor and Codex?
Yes. Trade Study Report uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.
What is inside the Trade Study Report skill?
The SKILL.md covers Inputs, Workflow, Step 1 — Load the matrix, Step 2 — Ingest analysis results, Step 3 — Compute weighted totals and rank, Step 4 — Run the sensitivity analysis, and the skill folder has 4 files.
What is a good alternative to Trade Study Report?
Competitive Matrix by alirezarezvani is the highest-ranked similar skill from another creator, with an Alyn Score of 63 compared to 79 for Trade Study Report.
Is Trade Study Report free?
Trade Study Report is open source on GitHub under the Apache-2.0 license. It is free to install; check the license before commercial use.
Who made Trade Study Report?
Trade Study Report is published by Anthropic in the anthropics/claude-plugins-official repository, together with 52 other skills.





