marklogic-fasttrack

marklogic-fasttrack is a skill for Claude Code, Codex from tternquist/marklogic-mcp. It costs 104 tokens per session (1,525 once invoked), scanned A, original, MIT.

A guide for building a React search interface on MarkLogic, a database with built-in search features. It helps define the search settings that control filters, date timelines, and map-based searches.

In plain words
What is it for?
Use it to configure faceted search, date ranges, and location filters, then create the React app that uses them.
Why use it?
It reduces the trial and error of connecting the interface to MarkLogic search. It also helps catch missing database indexes or rejected settings before the interface is built.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/tternquist/marklogic-mcp/marklogic-fasttrack
Any agent
npx skills add tternquist/marklogic-mcp --skill marklogic-fasttrack
Clone the repo
git clone --depth 1 https://github.com/tternquist/marklogic-mcp

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 marklogic-fasttrack

README.md
[![agentmods](https://agentmods.dev/badge/skills/tternquist/marklogic-mcp/marklogic-fasttrack.svg)](https://agentmods.dev/skills/tternquist/marklogic-mcp/marklogic-fasttrack)
Your own site
<a href="https://agentmods.dev/skills/tternquist/marklogic-mcp/marklogic-fasttrack"><img src="https://agentmods.dev/badge/skills/tternquist/marklogic-mcp/marklogic-fasttrack.svg" alt="Measured on agentmods" height="20"></a>
Per session 104 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,525 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00104 $0.01525
Opus 5 $0.00052 $0.00763
Sonnet 5 $0.00021 $0.00305
Haiku 4.5 $0.00010 $0.00153

Measured 4d ago against content hash 3edf5b1821bb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

marklogic-fasttrack 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 4d 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.

.claude/skills/marklogic-fasttrack/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MarkLogic FastTrack

FastTrack is a React component library over MarkLogic's Search API. The UI is driven almost entirely by a stored search options set — get that right and the components mostly configure themselves.

Order of work

  1. Confirm the indexes exist (ml_indexes_list). Every facet constraint needs one.
  2. Write the search options and store with ml_search_options_put.
  3. Verify server-side with ml_search before touching React.
  4. Scaffold the React app.

Skipping step 3 is the usual reason a FastTrack UI shows no facets — the options set was rejected or the index is missing, and the component just renders empty.

Constraint index rules

Prefer path indexes. For JSON content, a path-index with path //fieldName uses a range-path-index, creatable via admin:database-add-range-path-index through ml_eval_xquery.

json-property is the fallback — it needs a range-json-property-index, which is only creatable through the Management API on port 8002.

// string facet
{"name":"field","range":{"type":"xs:string","facet":true,"path-index":{"text":"//field"}}}

// numeric facet
{"name":"field","range":{"type":"xs:decimal","facet":true,"path-index":{"text":"//field"}}}

// date facet (with buckets)
{"name":"field","range":{"type":"xs:date","facet":true,"path-index":{"text":"//field"}}}

Dates stored as ISO strings (YYYY-MM-DD) should use xs:string, not xs:date — ISO strings sort chronologically, and this avoids a cast that will fail on any malformed value.

Geospatial (map widget) — a geo-elem-pair constraint with parent/lat/lon. Only add it if the schema actually has geo fields.

⚠ Bucket syntax: name, not label

CORRECT: {"name":"Under 80k","lt":"80000"}
CORRECT: {"name":"80-100k","ge":"80000","lt":"100000"}
WRONG:   {"label":"Under 80k","lt":"80000"}

label produces XDMP-VALIDATEMISSINGATTR and a 400 from the REST API. Every bucket needs a name.

Options skeleton

Read the full file on GitHub · 141 lines

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. 4d ago First seen · 141 lines · 104 tokens per session scan A 3edf5b1821bb

Subscribe to this mod's changes

marklogic-fasttrack is a skill published in the GitHub repository tternquist/marklogic-mcp (3 stars, last pushed 14d ago), licensed MIT. It adds 104 tokens to every session and 1,525 once invoked, about $0.0005 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 2026-08-31.

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