CWC Workshops is a collection of materials from Anthropic-run workshops on building and evaluating AI-assisted coding workflows. The workshops cover model selection, multi-agent systems, managed agents, and product development with coding agents. The catalogue entries are examples and teaching materials from those workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add anthropics/cwc-workshops --skill supplier-selectiongit clone --depth 1 https://github.com/anthropics/cwc-workshopsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/anthropics/cwc-workshops/supplier-selection)<a href="https://agentmods.dev/skills/anthropics/cwc-workshops/supplier-selection"><img src="https://agentmods.dev/badge/skills/anthropics/cwc-workshops/supplier-selection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/anthropics/cwc-workshops/supplier-selection"><img src="https://agentmods.dev/badge/skills/anthropics/cwc-workshops/supplier-selection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00925 |
| Opus 5 | $0.00016 | $0.00463 |
| Sonnet 5 | $0.00007 | $0.00185 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
supplier-selection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Supplier Selection
Ranking suppliers is arithmetic, not judgment. Compute it in Python via code execution — do not reason about it in prose.
Method
For a given SKU:
- Read
/mnt/user/data/supplier_catalog.csvand filter to rows matching the SKU. This gives you(supplier_id, unit_price, min_order_qty)for each candidate. - Join with
/mnt/user/data/suppliers.csvonsupplier_idto getlead_time_daysandreliability. - Normalize price and lead time across the candidates (min-max to [0,1], where 0 is best). Reliability is already on [0,1] where higher is better.
- Score each candidate:
score = 0.5 × (1 − norm_price) + 0.3 × (1 − norm_lead_time) + 0.2 × reliability - Pick the highest score. Tie-breaks: lowest
unit_price, then lowestlead_time_days, then alphabeticalsupplier_id.
Do this in code
Write and run a short Python script — don't call a tool per supplier, and don't compare quotes by describing them. Example shape:
import csv
sku = "SKU-0057"
catalog = [r for r in csv.DictReader(open("/mnt/user/data/supplier_catalog.csv")) if r["sku"] == sku]
suppliers = {r["supplier_id"]: r for r in csv.DictReader(open("/mnt/user/data/suppliers.csv"))}
# join, normalize, score, sort — print the winner as JSON
Supplier-specific overrides
These quirks are not in the catalog data. Apply them after computing the score; if one changes your pick, say so in the rationale.
| Supplier | Override |
|---|---|
| SUP-01 Cascade Distribution | Orders >500 units need 48h notice or they auto-split into two shipments — add to lead-time math for large POs. |
| SUP-02 Alpine Wholesale | Closed Dec 20 – Jan 3. POs in that window aren't acknowledged until Jan 4. Land holiday replenishment before Dec 15. |
| SUP-03 Backcountry Supply Co | Two short-ships on Tents & Shelter this year. Prefer an alternate for that category if lead is comparable. |
| SUP-04 Sierra Outfitters | Unlisted 3% price break at 250+ units. If recommended qty is 200–249, often worth rounding up. |
| SUP-05 Granite Gear Partners | West-coast DC only. Add 2–3 days to catalog lead time for WH-EAST deliveries. |
| SUP-07 Ridgecrest Imports | Import-only; lead times are port-congestion sensitive. Don't rely on stated lead for an urgent order. |
| SUP-09 Summit Source | MOQ is enforced strictly — they reject (not round up) below-MOQ POs. |
| SUP-12 Trailhead Mercantile | New on roster. Treat reliability as one notch lower than stated until 6 months of history. |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 71 lines · 33 tokens per session scan A 0d4f991cb39d
supplier-selection is a skill published in the GitHub repository anthropics/cwc-workshops (2,047 stars, last pushed 12d ago), licensed Apache-2.0. It adds 33 tokens to every session and 925 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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