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.
npx skills add JetXu-LLM/DocMason --skill retrieval-workflowgit clone --depth 1 https://github.com/JetXu-LLM/DocMasonWrote 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.
[](https://agentmods.dev/skills/jetxu-llm/docmason/retrieval-workflow)<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.
<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>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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
- Confirm that the published knowledge base exists with
docmason status --jsonwhen needed. - Run
docmason retrieve "<query>" --json --compactfor host-visible inspection.- when full nested unit or artifact detail is genuinely required, rerun full
--jsonto 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, orvalidate-kbwhile a lease-owning command is still active
- when full nested unit or artifact detail is genuinely required, rerun full
- 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, andcompare_coverage_bonus - when exact artifact fields such as
section_path,caption_text,continuation_group_ids,procedure_hints, orsemantic_labelsmatter, inspect a file-first full JSON capture or the published artifact sidecars rather than dumping the full raw payload into chat focus_render_assetswhen presentrecommended_hybrid_targetswhen 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-imageartifacts or unitsemantic_gap_hintsare present before assuming the KB has enough semantics already
- Narrow or widen the query by:
--document-type--source-id--top--graph-hops- when
reference_resolution.statusisexact, expect the source filter and any exact unit targeting to have already narrowed the candidate set decisively - when
reference_resolution.statusisapproximatebutunit_match_statusisexact, expect retrieval to narrow to the resolved source while still preserving the approximate notice - when
reference_resolution.statusisapproximateorunresolved, 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
- If the strongest results are weak or empty, say so explicitly instead of pretending the query succeeded.
- For compare-style retrieval, verify that more than one source survives the top support set before calling the bundle comparison-ready.
- Open the cited source, unit, artifact, and render assets before claiming confidence on difficult evidence judgments.
- When the task is moving toward a final answer or deliverable draft, return retrieval bundles to the main agent for provenance tracing,
grounded-answer, orgrounded-composition. - If you need to export a scratch evidence note and the user did not specify a destination, place it under
runtime/agent-work/.
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.
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.
- 9d ago First seen · 82 lines · 18 tokens per session scan A a9ef18052bce
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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