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Agent skill · Audited from source

Citation Injector

skill · WILLOSCAR/research-units-pipeline-skillsLicence not declaredAudited 19 Oct 2026 · source 81994516a430

★ 513pushed 14 days ago
✓SAFEGrade B · 89/100 · 19 Oct 2026 · 8199451
513repo stars · whole WILLOSCAR/research-units-pipeline-skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 81994516a430 and found no filesystem, network or shell access and no hard-coded secrets. What it does: APPLIES/consumes a `citation-diversifier` budget report (`output/CITATION_BUDGET_REPORT.md`) to inject *in-scope* citations into an existing draft (NO NEW FACTS), so the run passes the global unique-citation gate…

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Cite this page

ModelsAtlas. “Citation Injector (WILLOSCAR/research-units-pipeline-skills)”. Retrieved 19 Oct 2026. https://modelsatlas.com/skills/willoscar/citation-injector

Trust audit

Audit 0.4.1 · source read 19 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high1 medium2 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityWARN2
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS1
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass, no license.

Findings (3)

LOWInventory / provenanceinv.no_license
F-13 Inventory / provenanceCWE-1104Layer L0
Why
no LICENSE file and no repo licence
Fix
add a licence
LOWInsecure cryptocrypto.weak_hash · scripts/run.py:110
F-09 Insecure cryptoCWE-327 · CWE-338Layer L1
h = int(hashlib.sha1(str(seed or "").encode("utf-8", errors="ignore")).hexdigest()[:8], 16)
Why
No further detail recorded for this rule.
Fix
—

Audit 0.4.1 · source sha 81994516a430 · 19 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • PublisherWILLOSCAR GitHub userOwner of the repository this skill is read from
  • Source folderWILLOSCAR/research-units-pipeline-skills/.codex/skills/citation-injectorThe exact folder we audited
  • LicenceNot declaredAs the repository states it
  • Commit pinned for this verdict81994516a430A new audit runs when the source changes
  • Repository statusNot archivedLast push 14 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: APPLIES/consumes a `citation-diversifier` budget report (`output/CITATION_BUDGET_REPORT.md`) to inject *in-scope* citations into an existing draft (NO NEW FACTS), so the run passes the global unique-citation gate…

---
name: citation-injector
description: "APPLIES/consumes a `citation-diversifier` budget report (`output/CITATION_BUDGET_REPORT.md`) to inject *in-scope* citations into an existing draft (NO NEW FACTS), so the run passes the global unique-citation gate without citation dumps."
---

# Citation Injector (deterministic baseline edits; budget-as-constraints)

## Triggers & routing

- **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.


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 such as `This subsection discusses` or `Next, we examine`.
- 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)
- `The same design pressure appears in nearby systems (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

- `uv run python .codex/skills/citation-injector/scripts/run.py --workspace <workspace>`

### 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:
  - `uv run python .codex/skills/citation-injector/scripts/run.py --workspace <workspace>`

Excerpt, first 5,862 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 8199451

Download folder ↗
git clone https://github.com/WILLOSCAR/research-units-pipeline-skills
git -C research-units-pipeline-skills checkout 81994516a430

The author documents no install command, so this uses the repository directly. Our verdict covers commit 81994516a430 only.

Works in which agents?

What its own text says, not a test

AgentStatusMore
CodexMentioned in its text, not testedSkills for Codex · About Codex
“Mentioned” means the skill’s text names the agent. We have not run it there.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 81994516a430

README badge

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Questions about Citation Injector

What does the Citation Injector skill do?
Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrails. Evidence-first methodology prevents hollow writing through structured intermediate artifacts.
Is Citation Injector safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Citation Injector access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does Citation Injector work with?
Its documentation mentions codex. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (81994516a430), read on 2026-10-19. The repository is watched, and a new audit runs when it changes — this is the first audit.

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