mthds-run
Run MTHDS methods
Execute MTHDS method bundles and interpret their JSON output.
Process
Step 0 — CLI Check (mandatory, do this FIRST)
Run mthds-agent --version. The minimum required version is 0.1.0 (declared in this skill's front matter as min_mthds_version).
- If the command is not found: STOP. Do not proceed. Tell the user:
The
mthds-agentCLI is required but not installed. Install it with:npm install -g mthdsThen re-run this skill.
- If the version is below 0.1.0: STOP. Do not proceed. Tell the user:
This skill requires
mthds-agentversion 0.1.0 or higher (found X.Y.Z). Upgrade with:npm install -g mthds@latestThen re-run this skill.
- If the version is 0.1.0 or higher: proceed to the next step.
Do not write .mthds files manually, do not scan for existing methods, do not do any other work. The CLI is required for validation, formatting, and execution — without it the output will be broken.
Step 0.5 — Pipelex Runtime Check (mandatory)
Running methods requires the Pipelex runtime to be installed and configured.
First, check if pipelex-agent is available:
pipelex-agent --version
- If the command is not found: STOP. Tell the user:
The Pipelex runtime is not installed. Install it with:
curl -fsSL https://pipelex.com/install.sh | sh
Then, if pipelex-agent is installed, check configuration health:
mthds-agent pipelex doctor
- If the doctor reports config issues (missing backends, missing API keys) AND the user is requesting a live run (not
--dry-run): STOP. Tell the user:
Pipelex needs to be configured with inference backends before running methods. Use
/pipelex-setupfor guided configuration.
-
If the user is requesting a dry run (
--dry-run): config issues are OK — dry runs work without backend configuration. Proceed. -
If healthy: proceed to Step 1.
Step 1: Identify the Target
| Target | Command |
|---|---|
| Pipeline directory (recommended) | mthds-agent pipelex run bundle <bundle-dir>/ |
| Specific pipe in a directory | mthds-agent pipelex run bundle <bundle-dir>/ --pipe my_pipe |
| Bundle file directly | mthds-agent pipelex run bundle bundle.mthds -L <bundle-dir>/ |
| Pipe by code from library | mthds-agent pipelex run bundle my_pipe |
Directory mode (recommended): Pass the pipeline directory as target. The CLI auto-detects
bundle.mthds,inputs.json, and sets-Lautomatically — no need to specify them explicitly. This also avoids namespace collisions with other bundles.
Step 2: Prepare Inputs and Check Readiness
Fast path — inputs just prepared
If inputs were already prepared during this conversation — via /mthds-inputs (user-data, synthetic, or mixed strategy), or by manually assembling inputs.json with real values earlier in this session — skip the schema fetch and readiness check. The inputs are ready. Proceed directly to Step 3 with a normal run.
This applies when you just wrote or saw inputs.json being written with real content values. It does NOT apply after /mthds-build (which saves a placeholder template) or after /mthds-inputs with the template strategy.
Full check — cold start
If /mthds-run is invoked without prior input preparation in this session, perform the full readiness check:
Get the input schema for the target:
mthds-agent pipelex inputs bundle bundle.mthds
Output:
{
"success": true,
"pipe_code": "process_document",
"inputs": {
"document": {
"concept": "native.Document",
"content": {"url": "url_value"}
},
"context": {
"concept": "native.Text",
"content": {"text": "text_value"}
}
}
}
Fill in the content fields with actual values. For complex inputs, use the /mthds-inputs skill.
Input Readiness Check
Before running, assess whether inputs are ready. This prevents runtime failures from placeholder values.
No inputs required: If mthds-agent pipelex inputs bundle <file>.mthds returns an empty inputs object ({}), inputs are ready — skip to Step 3.
Inputs required: If inputs exist, check inputs.json for readiness:
- Does
inputs.jsonexist in the bundle directory? - If it exists, scan all
contentvalues for placeholder signals:- Template defaults:
"url_value","text_value","number_value","integer_value","boolean_value", or any value matching the pattern*_value - Angle-bracket placeholders: values containing
<...>(e.g.<path-to-cv.pdf>,<your-text-here>) - Non-existent file paths:
urlfields pointing to local files that don't exist on disk
- Template defaults:
Readiness result:
- Ready:
inputs.jsonexists AND all content values are real (no placeholders, referenced files exist) → proceed to Step 3 with normal run - Not ready:
inputs.jsonis missing, OR contains any placeholder values → proceed to Step 3 with dry-run fallback
Step 3: Choose Run Mode
If inputs are not ready
Default to --dry-run --mock-inputs and inform the user:
"The inputs for this pipeline contain placeholder values (not real data). I'll do a dry run with mock inputs to validate the pipeline structure."
After the dry run, offer the user these options:
- Prepare real inputs — use
/mthds-inputsto fill in actual values, then re-run - Provide files — if the pipeline expects file inputs (documents, images), ask the user to supply file paths
- Keep dry run — accept the dry-run result as-is
Run modes reference
| Mode | Command | Use When |
|---|---|---|
| Dry run + mock inputs | mthds-agent pipelex run bundle <bundle-dir>/ --dry-run --mock-inputs |
Quick structural validation, no real data needed, or inputs not ready |
| Dry run with real inputs | mthds-agent pipelex run bundle <bundle-dir>/ --dry-run |
Validate input shapes without making API calls (auto-detects inputs.json) |
| Full run | mthds-agent pipelex run bundle <bundle-dir>/ |
Production execution (auto-detects inputs.json) |
| Full run inline | mthds-agent pipelex run bundle <bundle-dir>/ --inputs '{"theme": ...}' |
Quick execution with inline JSON inputs |
| Full run without graph | mthds-agent pipelex run bundle <bundle-dir>/ --no-graph |
Execute without generating graph visualization |
| Full run with memory | mthds-agent pipelex run bundle <bundle-dir>/ --with-memory |
When piping output to another method |
Graph by default: Execution graphs (
live_run.html/dry_run.html) are now generated automatically. Use--no-graphto disable.
Inline JSON for Inputs
The --inputs flag accepts both file paths and inline JSON. The CLI auto-detects: if the value starts with {, it is parsed as JSON directly. This is the fastest path — no file creation needed for simple inputs.
# Inline JSON
mthds-agent pipelex run bundle <bundle-dir>/ --inputs '{"theme": {"concept": "native.Text", "content": {"text": "nature"}}}'
# File path (auto-detected in directory mode)
mthds-agent pipelex run bundle <bundle-dir>/
Step 4: Present Results
After a successful run, always show the actual output to the user — never just summarize what fields exist.
Output format modes
The CLI has two output modes:
- Compact (default): stdout is the concept's structured JSON directly — no envelope, no
successwrapper. This is the primary output of the method's main concept. Parse the JSON directly for field access. - With memory (
--with-memory): stdout hasmain_stuff(withjson,markdown,htmlrenderings) +working_memory(all named stuffs and aliases). Use this when piping output to another method.
The output_file and graph_files are written to disk as side effects (paths appear in logs/stderr), not in compact stdout.
4a. Determine what to show
In compact mode (default), the output is the concept JSON directly. Show the fields to the user:
{
"clauses": [...],
"overall_risk": "high"
}
In --with-memory mode, the output structure depends on the pipe architecture:
if main_stuff is non-empty (not {} or null):
→ main_stuff is the primary output (single unified result)
else:
→ working_memory.root holds the primary output (multiple named results)
| Pipe Type | main_stuff present? |
What to show |
|---|---|---|
| PipeLLM, PipeCompose, PipeExtract, PipeImgGen, PipeSearch | Always | main_stuff |
| PipeSequence | Always (last step) | main_stuff |
| PipeBatch | Always (list) | main_stuff |
| PipeCondition | Always | main_stuff |
PipeParallel with combined_output |
Yes | main_stuff |
PipeParallel without combined_output |
No ({}) |
working_memory.root entries |
4b. Show the output content
In compact mode: show the JSON fields directly. For structured concepts, format for readability.
In --with-memory mode when main_stuff is present (most pipe types):
- Show
main_stuff.markdowndirectly — this is the human-readable rendering. Display it as-is so the user sees the full output. - For structured concepts with fields, also show
main_stuff.jsonformatted for readability.
In --with-memory mode when main_stuff is empty (PipeParallel without combined_output):
- Iterate
working_memory.rootand present each named result. - For each entry, show the
contentfield with its key as a label. - Example: "french_translation: Bonjour le monde" / "spanish_translation: Hola mundo"
For dry runs: Show the same output but clearly label it as mock/simulated data.
4c. Output file
- The CLI automatically saves the full JSON output next to the bundle (
live_run.jsonordry_run.json). - The output file path appears in runtime logs (stderr), not in compact stdout.
4d. Present graph files
- Graph visualizations are generated by default (
live_run.html/dry_run.html). Use--no-graphto disable. - The graph file path appears in runtime logs (stderr), not in compact stdout.
4e. Mention intermediate results
- If the pipeline has multiple steps, briefly note key intermediate values from
working_memory(e.g., "The match analysis intermediate step scored 82/100"). - Offer: "I can show the full working memory if you want to inspect any intermediate step."
4f. Suggest next steps
- Re-run with different inputs
- Adjust prompts or pipe configurations if output quality needs improvement
Step 5: Handle Errors
When encountering runtime errors, re-run with --log-level debug for additional context:
mthds-agent --log-level debug pipelex run bundle <bundle-dir>/ --inputs data.json
For all error types and recovery strategies, see Error Handling Reference.
Execution Graphs
Execution graph visualizations are generated by default alongside the run output. Use --no-graph to disable.
mthds-agent pipelex run bundle <bundle-dir>/
Graph files (live_run.html / dry_run.html) are written to disk next to the bundle. Their paths appear in runtime logs on stderr, not in compact stdout. When using --with-memory, graph_files is included in the returned JSON envelope.
Piping Methods
The run command accepts piped JSON on stdin when --inputs is not provided. This enables chaining methods:
mthds-agent pipelex run method extract-terms --inputs data.json --with-memory \
| mthds-agent pipelex run method assess-risk --with-memory \
| mthds-agent pipelex run method generate-report
When methods are installed as CLI shims, the same chain is:
extract-terms --inputs data.json --with-memory \
| assess-risk --with-memory \
| generate-report
- Use
--with-memoryon intermediate steps to pass the full working memory envelope. - The final step omits
--with-memoryto produce compact output. --inputsalways overrides stdin when both are present.- Upstream stuff names are matched against downstream input names. Method authors should name their outputs to match the downstream's expected input names.
Reference
- Error Handling — read when CLI returns an error to determine recovery
- MTHDS Agent Guide — read for CLI command syntax or output format details
- MTHDS Language Reference — read for .mthds syntax documentation
- Native Content Types — read when interpreting pipeline outputs or preparing input JSON, to understand the attributes of each content type