Skill: willoscar/citation-injector (version 1.0.0)

--- name: citation-injector description: 'Apply a `citation-diversifier` budget report by injecting *in-scope* citations into an existing draft (NO NEW FACTS), so the run passes the global unique-citation gate without citation dumps. **Trigger**: citation injector, apply citation budget, inject citations, add citations safely, 引用注入, 按预算加引用, 引用增密. **Use when**: `output/CITATION_BUDGET_REPORT.md` exists and you need to raise *global* unique citations (or reduce over-reuse) before `draft-polisher` / `pipeline-auditor`. **Skip if**: you need more papers/citations upstream (fix C1/C2 mapping first), or `citations/ref.bib` is missing. **Network**: none. **Guardrail**: NO NEW FACTS; do not invent citations; only inject keys present in `citations/ref.bib`; keep injected citations within each H3’s allowed scope (via the budget report); avoid citation-dump paragraphs (embed cites per work).' version: 0.1.0 metadata: openclaw: requires: anyBins: - python3 - python --- # Citation Injector (deterministic baseline 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 **conservative and scriptable**: - the script edits `output/DRAFT.md` directly using the budget report as constraints - injections stay evidence-neutral (NO NEW FACTS) and use only in-scope keys already listed for each H3 ## 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). 1) 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.` 2) Parenthetical grounding (short, low-risk) - `... (e.g., X [@a], Y [@b], Z [@c]).` 3) 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>.` 4) Decision-lens pointer - `For builders choosing between <A> and <B>, prior systems provide concrete instantiations on both sides (X [@a]; Y [@b]; Z [@c]).` 5) 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.` 6) 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 1) 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. 2) Inject in the right subsection - Use `outline/outline.yml` to confirm H3 ordering and ensure the injected sentence lands inside the correct `###` subsection. 3) 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`. 4) 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. 5) 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; deterministic injector + validator) You usually do not run this manually; it exists so a pipeline runner can deterministically apply a baseline injection and validate the target. ### Quick Start - `python 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 generate the budget report and want the script to apply the baseline injection: - `python scripts/run.py --workspace workspaces/<ws>`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)