citation-injector

Citation Injector (LLM-first edits; budget-as-constraints)

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Install skill "citation-injector" with this command: npx skills add willoscar/research-units-pipeline-skills/willoscar-research-units-pipeline-skills-citation-injector

Citation Injector (LLM-first edits; budget-as-constraints)

Purpose: make the pipeline converge when the draft is:

  • locally citation-dense but globally under-cited (too few unique keys), or

  • overly reusing the same citations across many subsections.

This skill is intentionally LLM-first:

  • you edit output/DRAFT.md using the budget report as constraints

  • the helper script is validation-only (it never injects prose)

Inputs

  • output/DRAFT.md

  • output/CITATION_BUDGET_REPORT.md (from citation-diversifier )

  • outline/outline.yml (H3 id/title mapping)

  • citations/ref.bib (must contain every injected key)

Outputs

  • output/DRAFT.md (updated in place)

  • output/CITATION_INJECTION_REPORT.md (PASS/FAIL + what you changed)

Non-negotiables (NO NEW FACTS)

  • Only inject keys listed for that H3 in the budget report.

  • Do not introduce new numbers, new benchmarks, or superiority claims.

  • Do not add narration templates (This subsection ... , Next, we ... ).

  • Do not produce cite dumps like [@a; @b; @c] as the only citations in a paragraph.

Paper-voice injection patterns (safe sentence shapes)

Use these as sentence intentions (paraphrase; do not copy verbatim).

  • Axis-anchored exemplars (preferred)

  • Systems such as X [@a] and Y [@b] instantiate <axis/design point>, whereas Z [@c] explores a contrasting point under a different protocol.

  • Parenthetical grounding (short, low-risk)

  • ... (e.g., X [@a], Y [@b], Z [@c]).

  • Cluster pointer + contrast hint

  • Representative implementations span both <cluster A> (X [@a], Y [@b]) and <cluster B> (Z [@c]), suggesting that the trade-off hinges on <lens>.

  • Decision-lens pointer

  • For builders choosing between <A> and <B>, prior systems provide concrete instantiations on both sides (X [@a]; Y [@b]; Z [@c]).

  • Evaluation-lens pointer (still evidence-neutral)

  • Across commonly used agent evaluations, systems such as X [@a] and Y [@b] illustrate how <lens> is operationalized, while Z [@c] highlights a different constraint.

  • Contrast without list voice

  • While many works operationalize <topic> via <mechanism> (X [@a]; Y [@b]), others treat it as <alternative> (Z [@c]), which changes the failure modes discussed later.

Anti-patterns (high-signal “budget dump” voice)

Avoid these stems (they read like automated injection):

  • A few representative references include ...

  • Notable lines of work include ...

  • Concrete examples include ...

If your draft contains these, rewrite them immediately using the patterns above (keep citation keys unchanged).

Placement guidance

  • Prefer inserting citations where the subsection already states a concrete contrast or decision lens.

  • If you must add a new sentence/mini-paragraph, place it early (often after paragraph 1) so it reads as positioning, not as an afterthought.

  • Keep injections subsection-specific: mention the subsection lens (H3 title / contrast_hook ) so the same sentence cannot be copy-pasted into every H3.

Workflow

  • Read the budget report (output/CITATION_BUDGET_REPORT.md )

  • Treat Global target (policy; blocking) as the PASS line for the pipeline gate (derived from queries.md:citation_target ; A150++ default: recommended ).

  • If Gap: 0 , do nothing: write a short PASS report and move on.

  • Otherwise, for each H3 with suggested keys, pick enough keys to close the gap to target:

  • small gaps: 3-6 keys / H3

  • A150++ gaps: often 6-12 keys / H3 Prefer keys that are unused globally and avoid repeating the same new keys across many H3s.

  • Inject in the right subsection

  • Use outline/outline.yml to confirm H3 ordering and ensure the injected sentence lands inside the correct ### subsection.

  • Inject with paper voice

  • Prefer one short, axis-anchored sentence over a long enumerator sentence.

  • Keep injections evidence-neutral (NO NEW FACTS) and avoid new numbers.

  • Before you commit an injected key, confirm it exists in citations/ref.bib .

  • Write output/CITATION_INJECTION_REPORT.md

  • Record which H3s you touched and which keys were added.

  • Mark - Status: PASS only when the global target is met.

  • Verify

  • Rerun the validator script (below) to recheck the global target.

  • Then run draft-polisher to smooth any residual injection voice (citation keys must remain unchanged).

Done criteria

  • output/CITATION_INJECTION_REPORT.md exists and is - Status: PASS .

  • pipeline-auditor no longer FAILs on “unique citations too low”.

Script (optional; validation only)

You usually do not run this manually; it exists so a pipeline runner can deterministically validate the target.

Quick Start

  • python .codex/skills/citation-injector/scripts/run.py --workspace workspaces/<ws>

All Options

  • --workspace <dir>

  • --unit-id <U###> (optional; for logs)

  • --inputs <semicolon-separated> (rare override; prefer defaults)

  • --outputs <semicolon-separated> (rare override; default validates output/CITATION_INJECTION_REPORT.md )

  • --checkpoint <C#> (optional)

Examples

  • After you manually inject citations and write the report:

  • python .codex/skills/citation-injector/scripts/run.py --workspace workspaces/<ws>

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