write-economics-conclusion

write-economics-conclusion is a skill for Codex from mimaowang/econ-writing-skills. It costs 117 tokens per session (2,706 once invoked), scanned A, original, MIT.

A writing guide for producing the conclusion of an economics research paper—the final section that summarizes what the study established, why it matters, and where its evidence ends.

In plain words
What is it for?
Use it to draft, rewrite, shorten, or check conclusions for empirical, theoretical, or structural economics papers.
Why use it?
It helps keep the ending grounded in the paper's actual results instead of repeating the introduction or making claims the evidence cannot support.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: positional $N argument.

Good fit Use it to draft, rewrite, shorten, or check conclusions for empirical, theoretical, or structural economics papers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mimaowang/econ-writing-skills/write-economics-conclusion
Install

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.

Any agent
npx skills add mimaowang/econ-writing-skills --skill write-economics-conclusion
Clone the repo
git clone --depth 1 https://github.com/mimaowang/econ-writing-skills

Made for: Codex.

Wrote 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.

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README.md
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Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,706 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00117 $0.02706
Opus 5.5 $0.00047 $0.01082
Sonnet 5.5 $0.00023 $0.00541
Haiku 4.5 $0.00012 $0.00271

Measured 2mo ago against content hash 77049a12d33b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

write-economics-conclusion 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 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_output.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/write-economics-conclusion/SKILL.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Write an Economics Conclusion

Create the clean snapshot a reader should carry away from the paper: what the paper established, why it matters, and where the claim stops. Synthesize rather than repeat. Treat every extension beyond the results—mechanism, external validity, policy, and future work—as evidence-dependent.

Load the required knowledge

Before drafting, rewriting, or auditing, read all four references:

  1. references/evidence-protocol.md — manuscript reading, evidence ledger, causal language, conflicts, and missing information.
  2. references/conclusion-knowledge.md — the complete guide-derived principles, rationales, conditions, and anti-patterns.
  3. references/composition-and-length.md — module selection, natural order, transitions, paper-type branches, and elastic length.
  4. references/quality-and-sources.md — final audit, scoring rules, Top Five calibration, and provenance.

These references are mandatory. Follow the target journal and any separate Discussion-section convention before applying default length guidance.

Non-negotiable rules

  • Base the conclusion on claims delivered by the manuscript body, not merely promised in the introduction.
  • Never add a result, coefficient, mechanism, limitation, citation, counterfactual, future project, or policy claim that the supplied material does not support.
  • Distinguish identified mechanisms, model-implied mechanisms, evidence consistent with a channel, suggestive evidence, and author speculation.
  • Preserve mechanism strength exactly. If the source is only consistent with, supportive, or suggestive, do not write principal/main channel, drives, explains, accounts for, operates through, or a causal because unless separately supported.
  • Map every explanatory clause, appositive, modifier, adjective, and comparison—not only the sentence's main result. A correct main clause does not license an unsupported where, because, especially when, or reflecting explanation.
  • Match causal language to the design and external-validity language to the studied population, period, and institution.
  • Use only the few numbers needed to preserve economic magnitude or a policy tradeoff; verify every component.
  • Treat a number's denominator, baseline, comparison, and normalization as separate facts. Never infer of baseline or another denominator from nearby context.
  • Preserve every uncertainty operator on a null result. No detectable effect may not become no effect, unchanged, unaffected, without reducing/eroding/harming, preserved, or did not harm; every restatement must carry its own detection and proxy qualifications.
  • Treat low-cost, large, substantial, modest, meaningful, efficient, and similar evaluations as factual comparisons. Use them only with a reported benchmark or explicit source characterization.
  • Apply a closed-world paraphrase rule: a smoother expression is eligible only if the source entails it without adding scope, causal force, mechanism status, measurement meaning, evaluation, or centrality.
  • Do not convert a robustness exercise into a contribution or a caveat into proof that the concern is resolved.
  • Keep the formal conclusion in English by default. Use the user's language for necessary questions or risk notes.
  • Do not modify the source manuscript unless explicitly asked.

Read the full file on GitHub · 156 lines

Changes

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.

  1. 2mo ago First seen · 156 lines · 117 tokens per session scan A 77049a12d33b

Subscribe to this mod's changes

write-economics-conclusion is a skill published in the GitHub repository mimaowang/econ-writing-skills (6 stars, last pushed 3mo ago), licensed MIT. It adds 117 tokens to every session and 2,706 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-31.

Related

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write-economics-conclusion next to 6 skills from other repositories
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write-economics-conclusionmimaowang/econ-writing-skillsSkill63mo agoMITA117Codex
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