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Oma Academic Writing

OrganizationPopular
first-fluke
oma-academic-writing

Draft and revise academic prose against a rubric, evidence, and citation requirements. Use for essays, reports, literature reviews, or academic style audits.

Overview

Publisherfirst-fluke
Repositoryoh-my-agent
Skill nameoma-academic-writing
Stars
1.3K
Forks
149
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by first-fluke on GitHub. Read the source before you install it.

Installation

Install the Oma Academic Writing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/first-fluke/oh-my-agent.git /tmp/oh-my-agent
mkdir -p .claude/skills
cp -r /tmp/oh-my-agent/skills/oma-academic-writing .claude/skills/oma-academic-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oma Academic Writing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Oma Academic Writing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Oma Academic Writing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Academic Writing: Publication-Grade English Prose

Scheduling

Goal

Produce, revise, and audit publication-grade academic English prose so that every output simultaneously satisfies the Sentence Structure Protocol, Verb Protocol, Hedging Protocol, and Anti-AI Compliance Checklist, with every claim mapped to verifiable evidence.

Intent signature

  • "draft this essay / report / executive summary / conclusion / literature review"
  • "rewrite this paragraph in academic English"
  • "polish this draft to top-band quality" / "revise to match the rubric"
  • "run an anti-AI audit on this prose"
  • "check sentence structure variety" / "fix monotonous rhythm"
  • "the prose sounds AI-generated, make it pass"
  • "verify claims against evidence" / "reverse outline this section"

When to use

  • Drafting or revising academic reports, essays, or analysis sections
  • Writing executive summaries, conclusions, or literature reviews
  • Rewriting AI-sounding prose into natural academic English
  • Polishing draft text to achieve top-band rubric quality (HD, A, top-band, etc.)
  • Reviewing prose for sentence variety, verb quality, hedging, and anti-AI compliance
  • Any task requiring formal academic English output bound by a rubric

When NOT to use

  • Translation tasks → use oma-translation
  • Source discovery, citation gathering, or scholarly literature search → use oma-scholar
  • Rubric / assignment-spec parsing and task decomposition → use oma-pm
  • Code documentation, README, or API reference text → use the relevant domain skill (oma-frontend, oma-backend, oma-mobile, oma-db, etc.)
  • Informal communication, chat, or marketing copy → no skill needed
  • Non-English academic writing → call oma-translation for the target language after drafting in English

Expected inputs

  • mode: one of draft | revise | review
  • rubric_or_constraint: assignment brief, rubric file, or word/structure limits (path or inline text)
  • existing_draft: prior text to revise or audit (path or inline text); required for revise and review
  • source_data: available evidence, figures, citations the writer may use
  • target_register: defaults to formal academic English with American spelling (en-US)

Expected outputs

  • draft mode: section heading + drafted prose + Writing Notes (sentence mix, key verbs, anti-AI flags resolved, paragraph lengths) + Claim-Evidence Map
  • revise mode: original block, revised block, list of specific changes (verb upgrades, structure variation, anti-AI fixes)
  • review mode: PASS/FAIL Compliance Report across Sentence Structure, Verb Quality, Anti-AI, Specificity, Hedging, Paragraph Clarity, Rhythm/Burstiness, Claim-Evidence Alignment, plus recommended fixes

Dependencies

  • ../_shared/core/anti-ai-prose.md and resources/anti-ai-checklist.md: common diagnostics and academic constraints; load together for prose audits
  • resources/sentence-structure-reference.md: four sentence types, length targets, common errors
  • resources/academic-verb-tiers.md: meaning- and evidence-based verb guidance
  • resources/hedging-guide.md: calibrated certainty expressions matched to evidence strength
  • ../_shared/core/context-loading.md: task-relevant resource loading
  • ../_shared/core/quality-principles.md: shared quality bar

Control-flow features

  • Mode branching: draft vs revise vs review produce different output formats and pass sequences
  • Rubric-quote gate: refuses to apply a rule until the literal constraint text is quoted from the source
  • Citation gap branch: when a claim lacks evidence, weaken or remove rather than fabricate; optionally hand off to oma-scholar
  • Language branch: non-English target hands off to oma-translation after the English pass
  • Iterative AUDIT: every fix loops back through the anti-AI checklist before emit

Structural Flow

Entry

  1. Identify the mode (draft, revise, review) and the rubric source.
  2. Quote the exact constraint text (word limits, structural requirements, mandatory sections, rubric rows) before applying any rule.
  3. If revising or reviewing, read the existing draft in full first; if drafting, confirm available source data and citations.
  4. Index resources/ and identify any claims that need a more precise verb or hedge.
  5. Apply the literal-first principle before any drafting: prefer direct statement over metaphor and flourish. When a literal phrase is available, use it.

Scenes

  1. PREPARE: load rubric, existing draft, source data; record quoted constraints and note claims whose verbs or hedges need attention.
  2. ACQUIRE: read resources/sentence-structure-reference.md, academic-verb-tiers.md, and hedging-guide.md only for the patterns relevant to the current section.
  3. ACT: write or revise prose with sentence variety, accurate verb choice, evidence-matched hedging, clear paragraphing, and direct statements. Keep a common verb when it is the clearest accurate choice.
  4. VERIFY: apply the shared prose diagnostics and academic checklist; use reverse outlining and the Claim-Evidence Map to identify unsupported claims. In review mode, report findings without rewriting the draft.
  5. FINALIZE: read-aloud test, cohesion check, specificity audit, word-count verification, paragraph-length variation, rhythm check; emit per the mode's output format.

Transitions

  • If a rubric line is ambiguous → quote it back to the user and ask for interpretation; do not infer combined rules.
  • If a claim cannot be supported by available evidence → weaken with hedging or remove; if a citation gap is structural, NOTIFY oma-scholar.
  • If the target language is non-English → finish the English pass, then hand off to oma-translation.
  • If the same anti-AI flag survives one fix attempt → restructure the surrounding two sentences instead of word-substitution alone.
  • If an output mode mismatch is detected (e.g., user asked for review but supplied a fresh prompt) → confirm the mode before producing output.

Failure and recovery

FailureRecovery
Word count over / under targetCut filler adverbs and redundant qualifiers, or expand with supporting evidence; re-run audit
Repeated syntax obscures the argumentRevise the affected sentences for clarity using shared rhythm guidance; preserve clear sentences
Rubric requirement unclearQuote exact rubric text and ask user; do not combine rules
Claim lacks evidenceAdd citation, hedge to match weaker evidence, or remove the claim entirely
Hedging miscalibratedReplace double hedges; align hedge strength with resources/hedging-guide.md evidence-level table
Verb is vagueName the action, method, result, or evidence only if that makes the claim clearer
Repeated paragraph structure hinders progressionReorganize the affected argument without inserting a paragraph solely to vary length

Exit

  • Success: every protocol PASSes, the Claim-Evidence Map has no unsupported entries, word count complies, and the mode-specific output format is fully populated.
  • Partial success: emit prose with explicit needs evidence / pending citation markers and report which protocol items remain at risk; flag handoff candidates.
  • Failure: refuse to emit and report the blocking ambiguity (rubric quote missing, source data absent, contradictory constraints).

Logical Operations

Actions

ActionSSL primitiveEvidence
Read rubric / constraint and quote literal textREADRubric file or assignment brief
Read existing draft (revise/review modes)READDraft file or inline text
Index resources for the current sectionREADresources/{anti-ai-checklist,sentence-structure-reference,academic-verb-tiers,hedging-guide}.md
Select sentence mix and evidence-appropriate wordingSELECTSentence-structure and verb guidance
Plan paragraph as Topic-Support-ConcludeINFEROutline notes
Draft / revise prose under all four protocolsWRITEGenerated prose
Audit prose against anti-AI checklistVALIDATEresources/anti-ai-checklist.md
Reverse outline + build Claim-Evidence MapVALIDATEMapping table
Weaken or remove unsupported claimsWRITERevised claim line
Compare original vs revised (revise mode)COMPAREDiff block
Hand off non-English targetNOTIFYoma-translation
Hand off citation gapNOTIFYoma-scholar
Hand off ambiguous rubric / specNOTIFYoma-pm
Emit per mode output formatWRITEFinal artifact
Report compliance statusNOTIFYPASS/FAIL summary or Writing Notes block

Tools and instruments

  • Read / Edit / Write for draft and rubric files
  • resources/anti-ai-checklist.md, sentence-structure-reference.md, academic-verb-tiers.md, hedging-guide.md
  • Topic-Support-Conclude paragraph template (inline)
  • Claim-Evidence Map (inline 3-column table: Claim / Evidence / Status)
  • Output-format blocks per mode (Draft / Revision / Review)

Canonical workflow path

  1. READ rubric/draft and quote the exact literal constraint text; pin word limits, mandatory sections, and rubric rows.
  2. PLAN each paragraph as Topic-Support-Conclude; identify where evidence strength or a vague claim calls for a more precise verb.
  3. DRAFT prose with sentence variety, clear verb choice, hedging, and Topic-Support-Conclude structure.
  4. AUDIT with ../_shared/core/anti-ai-prose.md and resources/anti-ai-checklist.md. Fix supported defects in draft/revise mode; in review mode, quote the passage, identify the defect, and recommend a local fix without a full rewrite or AI-authorship estimate.
  5. REVERSE-OUTLINE the section and build the Claim-Evidence Map; weaken or remove any unsupported claim.
  6. POLISH with read-aloud, cohesion, specificity, word-count, rhythm, and paragraph-length-variation checks; emit in the mode's output format.

Resource scope

ScopeResource target
LOCAL_FSRubric, existing draft, generated prose output
CODEBASEresources/ 4 reference files, _shared/core/{context-loading,quality-principles}.md
MEMORYMode, quoted constraints, wording decisions, anti-AI flags resolved, Claim-Evidence Map

Preconditions

  • A rubric / constraint or an existing draft (or both) is provided.
  • The target register is academic English. If the final deliverable is non-English, the user has agreed to a downstream oma-translation handoff.
  • The source data needed to support claims is available, or unsupported claims are explicitly allowed to be weakened or removed.

Effects and side effects

  • Writes drafted, revised, or reviewed prose to the user's working location (file or inline).
  • Does not modify resources/ reference files.
  • Does not fetch external citations; defers to oma-scholar when discovery is required.
  • May NOTIFY adjacent skills but does not auto-spawn them; user or workflow drives the actual handoff.

Guardrails

  1. Every sentence must be verifiable; never fabricate data, statistics, or citations.
  2. Quote-before-judgment: cite the literal constraint or rubric text before applying any rule.
  3. Never combine distinct rules to invent a new constraint; apply rules exactly as written.
  4. Choose verbs for their exact meaning and support. Keep common verbs when they are accurate and natural; replace a vague verb only when the new wording states a relevant distinction without inflating the claim.
  5. Never place 3+ sentences of the same structural type consecutively; vary length (short 8–15, medium 16–25, long 26–40 words) and openers.
  6. Match hedge strength to evidence strength per hedging-guide.md; never use absolute claim words (definitely, clearly, obviously) outside mathematical facts; never first-person I think / I believe.
  7. Apply common prose diagnostics with the academic checklist's evidence and register exceptions. Vocabulary counts trigger contextual review, not automatic replacement of precise terms.
  8. Em dashes ≤ 1 per paragraph; semicolons ≤ 2 per 1000 words; sentence-case headers; no didactic disclaimers (It is important to note) or summary phrases (In summary, Overall).
  9. Every claim must map to evidence in the Claim-Evidence Map; weaken or remove unsupported claims rather than emit them.
  10. Read aloud before emit; if a sentence does not flow naturally, restructure it.
  11. Apply the shared mannered-prose guidance with the academic checklist's literal-statement requirement.

References

  • Common prose diagnostics: ../_shared/core/anti-ai-prose.md (load with the academic checklist for prose audits)
  • Academic audit constraints: resources/anti-ai-checklist.md
  • Sentence-structure reference: resources/sentence-structure-reference.md
  • Academic verb tiers: resources/academic-verb-tiers.md
  • Hedging guide: resources/hedging-guide.md
  • Shared context loading: ../_shared/core/context-loading.md
  • Shared quality principles: ../_shared/core/quality-principles.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Oma Academic Writing AI skill do?

Draft and revise academic prose against a rubric, evidence, and citation requirements. Use for essays, reports, literature reviews, or academic style audits.

Why use Oma Academic Writing on TypingMind?

Because you install it once and use it with any model. Oma Academic Writing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Oma Academic Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/first-fluke/oh-my-agent/tree/main/skills/oma-academic-writing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Oma Academic Writing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Oma Academic Writing?

As many as you like. As long as a model supports skills, you can use Oma Academic Writing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Oma Academic Writing AI skill free?

Yes. It is published on GitHub by first-fluke under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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