retrieval-workflow

retrieval-workflow is a skill for Claude Code, Codex from JetXu-LLM/DocMason. It costs 18 tokens per session (1,292 once invoked), scanned A, original, Apache-2.0.

A workflow for retrieving ranked evidence bundles from a published DocMason knowledge base. DocMason is a local knowledge system that stores organized source evidence.

In plain words
What is it for?
It helps search the knowledge base, return compact structured results, and inspect fuller evidence details when needed.
Why use it?
It helps locate the strongest available evidence for a question instead of relying on unsupported guesses. It also checks whether the local knowledge base is available.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps search the knowledge base, return compact structured results, and inspect fuller evidence details when needed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jetxu-llm/docmason/retrieval-workflow
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add JetXu-LLM/DocMason --skill retrieval-workflow
Clone the repo
git clone --depth 1 https://github.com/JetXu-LLM/DocMason

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for retrieval-workflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/jetxu-llm/docmason/retrieval-workflow/github.svg)](https://agentmods.dev/skills/jetxu-llm/docmason/retrieval-workflow)
Your own site
<a href="https://agentmods.dev/skills/jetxu-llm/docmason/retrieval-workflow"><img src="https://agentmods.dev/badge/skills/jetxu-llm/docmason/retrieval-workflow/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for retrieval-workflow

Your own site · 80×15
<a href="https://agentmods.dev/skills/jetxu-llm/docmason/retrieval-workflow"><img src="https://agentmods.dev/badge/skills/jetxu-llm/docmason/retrieval-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,292 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.01292
Opus 5 $0.00009 $0.00646
Sonnet 5 $0.00004 $0.00258
Haiku 4.5 $0.00002 $0.00129

Measured 9d ago against content hash a9ef18052bce, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

retrieval-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/canonical/retrieval-workflow/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Retrieval Workflow

Use this skill when the task is to retrieve the strongest published evidence bundles for a question or topic.

This is an evidence-focused workflow. Use it directly for explicit evidence requests, or let ask route here automatically.

Direct public retrieve remains a legal operator evidence surface. It does not substitute for canonical ask when the user is really asking for ordinary answer completion.

Required Capabilities

  • local file access
  • shell or command execution
  • ability to inspect structured JSON output

If the agent cannot run local commands or inspect the published file-only knowledge base, stop and explain that reliable retrieval is not possible.

Procedure

  1. Confirm that the published knowledge base exists with docmason status --json when needed.
  2. Run docmason retrieve "<query>" --json --compact for host-visible inspection.
    • when full nested unit or artifact detail is genuinely required, rerun full --json to a local file and inspect it selectively instead of streaming the raw payload into the live chat context
    • keep user-native source references inside the freeform query rather than inventing internal source IDs when the user already knows a file name, path, page, slide, sheet, or heading
    • keep DocMason workspace commands sequential inside the same workspace session; do not overlap retrieve, trace, sync, status, or validate-kb while a lease-owning command is still active
  3. Inspect:
    • reference_resolution
    • ranked source bundles
    • compact bundle fields such as matched_unit_ids, matched_artifact_ids, matched_overlay_unit_ids, and collection counts
    • artifact-aware score details such as structure_context_bonus, semantic_overlay_bonus, and compare_coverage_bonus
    • when exact artifact fields such as section_path, caption_text, continuation_group_ids, procedure_hints, or semantic_labels matter, inspect a file-first full JSON capture or the published artifact sidecars rather than dumping the full raw payload into chat
    • focus_render_assets when present
    • recommended_hybrid_targets when the published artifact plan still reports a hard-artifact semantic gap
    • graph-expansion summary fields
    • render references when relevant
    • any published-evidence plan fields such as preferred channels, matched channels, and whether published artifacts already look sufficient
    • for image-only or scanned PDF questions, check whether page-image artifacts or unit semantic_gap_hints are present before assuming the KB has enough semantics already
  4. Narrow or widen the query by:
    • --document-type
    • --source-id
    • --top
    • --graph-hops
    • when reference_resolution.status is exact, expect the source filter and any exact unit targeting to have already narrowed the candidate set decisively
    • when reference_resolution.status is approximate but unit_match_status is exact, expect retrieval to narrow to the resolved source while still preserving the approximate notice
    • when reference_resolution.status is approximate or unresolved, preserve the notice boundary rather than pretending the narrowing was exact
    • for artifact-hint or compare-style questions, prefer reformulations that keep the named table, chart, diagram, caption, or compared objects explicit
  5. If the strongest results are weak or empty, say so explicitly instead of pretending the query succeeded.
  6. For compare-style retrieval, verify that more than one source survives the top support set before calling the bundle comparison-ready.
  7. Open the cited source, unit, artifact, and render assets before claiming confidence on difficult evidence judgments.
  8. When the task is moving toward a final answer or deliverable draft, return retrieval bundles to the main agent for provenance tracing, grounded-answer, or grounded-composition.
  9. If you need to export a scratch evidence note and the user did not specify a destination, place it under runtime/agent-work/.

Read the full file on GitHub · 82 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 82 lines · 18 tokens per session scan A a9ef18052bce

Subscribe to this mod's changes

retrieval-workflow is a skill published in the GitHub repository JetXu-LLM/DocMason (135 stars, last pushed 5d ago), licensed Apache-2.0. It adds 18 tokens to every session and 1,292 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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