oma-academic-writer

Academic Writer: Publication-Grade English Prose Specialist

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-translator
• 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-translator 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

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

• resources/anti-ai-checklist.md: banned vocabulary, banned structural patterns, sentence-level checks
• resources/sentence-structure-reference.md: four sentence types, length targets, common errors
• resources/academic-verb-tiers.md: banned generic verbs and tiered academic-corpus replacements
• 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-translator 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 pre-select the verb tier and sentence mix targets for the section.

Scenes

1. PREPARE: load rubric, existing draft, source data; record quoted constraints; pick sentence mix and 2–3 anchor verbs per paragraph.
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 the four protocols enforced simultaneously: Sentence Structure (4 types, varied length, varied openers), Verb (no banned generic verbs as main verbs; prefer tier-1/2 academic verbs), Hedging (match strength to evidence), and Topic-Support-Conclude paragraphing.
4. VERIFY: audit against resources/anti-ai-checklist.md (vocabulary clusters, structural patterns, sentence-level checks); apply reverse outlining and build the Claim-Evidence Map; weaken or remove unsupported claims.
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-translator.
• 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

Failure	Recovery
Word count over / under target	Cut filler adverbs and redundant qualifiers, or expand with supporting evidence; re-run audit
Prose still sounds AI-generated after one pass	Vary sentence openers (subject, adverbial, participial, prepositional) and insert one short (≤10-word) sentence per paragraph; re-run audit
Rubric requirement unclear	Quote exact rubric text and ask user; do not combine rules
Claim lacks evidence	Add citation, hedge to match weaker evidence, or remove the claim entirely
Hedging miscalibrated	Replace double hedges; align hedge strength with resources/hedging-guide.md evidence-level table
Banned generic verb resists replacement	Restructure the sentence so the banned verb is not the main verb
Paragraph blocks are uniform 4–5 sentences	Insert a 2-sentence emphasis paragraph; re-run rhythm check

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

Action	SSL primitive	Evidence
Read rubric / constraint and quote literal text	READ	Rubric file or assignment brief
Read existing draft (revise/review modes)	READ	Draft file or inline text
Index resources for the current section	READ	resources/{anti-ai-checklist,sentence-structure-reference,academic-verb-tiers,hedging-guide}.md
Select sentence mix and 2–3 anchor verbs per paragraph	SELECT	Sentence-structure & verb-tier tables
Plan paragraph as Topic-Support-Conclude	INFER	Outline notes
Draft / revise prose under all four protocols	WRITE	Generated prose
Audit prose against anti-AI checklist	VALIDATE	resources/anti-ai-checklist.md
Reverse outline + build Claim-Evidence Map	VALIDATE	Mapping table
Weaken or remove unsupported claims	WRITE	Revised claim line
Compare original vs revised (revise mode)	COMPARE	Diff block
Hand off non-English target	NOTIFY	oma-translator
Hand off citation gap	NOTIFY	oma-scholar
Hand off ambiguous rubric / spec	NOTIFY	oma-pm
Emit per mode output format	WRITE	Final artifact
Report compliance status	NOTIFY	PASS/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; pre-select the sentence-type mix and 2–3 anchor verbs from academic-verb-tiers.md.
3. DRAFT prose with Sentence Structure, Verb, Hedging, and Topic-Support-Conclude protocols enforced simultaneously.
4. AUDIT the draft against resources/anti-ai-checklist.md (banned vocabulary clusters, banned structural patterns, sentence-level checks) and fix every flag.
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

Scope	Resource target
LOCAL_FS	Rubric, existing draft, generated prose output
CODEBASE	resources/ 4 reference files, _shared/core/{context-loading,quality-principles}.md
MEMORY	Mode, quoted constraints, anchor verbs per paragraph, 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-translator 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. Banned generic verbs (show, have, make, do, get, use, give, say, put, see, come, go, take, find, know, think, want, try, need, seem, become, keep, help, start, turn, bring, run, hold, set) must not appear as main verbs; replace per academic-verb-tiers.md.
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. Never cluster 3+ flagged AI-vocabulary items in a single paragraph; never insert promotional or inflated language; never append superficial -ing clauses for analysis.
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.

References

• Anti-AI checklist: 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