| name | mthds-run |
| description | Run MTHDS methods and interpret results. Use when user says "run this pipeline", "execute the workflow", "execute the method", "test this .mthds file", "try it out", "see the output", "dry run", or wants to execute any MTHDS method bundle and see its output. |
| min_mthds_version | 0.12.1 |
| allowed-tools | ["Bash","Read","Write","Edit","Grep","Glob"] |
Run MTHDS methods
Execute MTHDS method bundles and interpret their JSON output.
Process
Step 0 — Environment Check (mandatory, do this FIRST)
Run this command to check toolchain status:
bash -c '
# Pick the cached env-check from the plugin version with the highest semver.
# Matches both `mthds` (prod) and `mthds-dev` (dev) plugin caches. The padded
# segment trick keeps lex order = semver order so 0.10 does not sort below 0.9.
_best_f=""; _best_k=""
for f in "$HOME/.claude/plugins/cache/"*/mthds*/*/bin/mthds-env-check; do
[ -x "$f" ] || continue
_v="${f%/bin/*}"; _v="${_v##*/}"
_k=""; IFS=. read -ra _parts <<<"${_v%%[-+]*}"
for _p in "${_parts[@]}"; do _p=${_p%%[!0-9]*}; _k="${_k}$(printf %06d "${_p:-0}")"; done
[[ "$_k" > "$_best_k" ]] && { _best_f="$f"; _best_k="$_k"; }
done
[ -n "$_best_f" ] && exec "$_best_f" "0.12.1"
echo "MTHDS_ENV_CHECK_MISSING"
'
Interpret the output:
MTHDS_AGENT_MISSING → STOP. Do not proceed. Tell the user:
The mthds-agent CLI is required but not installed. Install it with:
npm install -g mthds
Then re-run this skill.
MTHDS_AGENT_VERSION_UNKNOWN → STOP. The installed mthds-agent returned an unparseable version. Tell the user:
Could not parse the output of mthds-agent --version. Your installation may be corrupt. Reinstall with:
npm install -g mthds@latest
Then re-run this skill.
-
MTHDS_AGENT_OUTDATED <installed> <required> → The installed mthds-agent is too old for this plugin. Do not hard-stop. Instead, tell the user their mthds-agent (v<installed>) is older than the required v<required>, then follow the upgrade flow to offer upgrading mthds-agent via npm install -g mthds@latest. After the upgrade flow completes (whether the user upgraded or declined), proceed to Step 1. The upgrade flow's "Not now" and "Never ask" options let users continue with current versions.
-
MTHDS_UPDATE_CHECK_FAILED ... → WARN. The update check command failed. Show the error output to the user. Suggest checking network connectivity and mthds-agent installation. Proceed to Step 1 with current versions.
-
UPGRADE_AVAILABLE ... → Read upgrade flow and follow the upgrade prompts before continuing to Step 1.
-
JUST_UPGRADED ... → Announce what was upgraded to the user, then continue to Step 1.
-
UP_TO_DATE ... → Proceed to Step 1. The line is a terse list of verified installed versions (e.g. UP_TO_DATE mthds-agent=0.10.0 plxt=0.4.0 plugin=0.12.0); if you mention the env-check in your preamble acknowledgement, relay the agent and plugin versions you saw. Two "explicit-quiet" variants share the same prefix and are also clean — proceed to Step 1 without warning, and do not relay the quiet state unless the user is troubleshooting:
UP_TO_DATE update-check=disabled — the user has turned update-check off via config.UP_TO_DATE update-check=snoozed — the user has an active snooze on the current version key; an upgrade would otherwise be available, but they explicitly asked for quiet.
-
No output → WARN. The env-check produced no output at all, which usually means mthds-agent itself is broken or the wrapper script bailed before printing. Tell the user the environment check could not be confirmed, then proceed cautiously to Step 1.
-
MTHDS_ENV_CHECK_MISSING → WARN. The env-check script was not found at either expected path. Tell the user the environment check could not run, but proceed to Step 1.
-
Any other output → WARN. The preamble produced unexpected output. Show it to the user verbatim. Proceed to Step 1 cautiously.
Do not write .mthds files manually, do not do any other work. The CLI is required for validation, formatting, and execution — without it the output will be broken.
Step 1 — Pipelex Runtime Check (mandatory)
Running methods requires the Pipelex runtime to be installed and configured.
The preamble (Step 0) already verifies mthds-agent and its managed binaries are present
and up to date. This step checks Pipelex-specific configuration health.
mthds-agent 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 /mthds-runner-setup for guided configuration.
Step 2: Identify the Target
| Target | Command |
|---|
| Pipeline directory (recommended) | mthds-agent run bundle <bundle-dir>/ |
| Specific pipe in a directory | mthds-agent run bundle <bundle-dir>/ --pipe my_pipe |
| Bundle file directly | mthds-agent run bundle bundle.mthds -L <bundle-dir>/ |
| Pipe by code from library | mthds-agent run bundle my_pipe |
Directory mode (recommended): Pass the pipeline directory as target. The CLI auto-detects bundle.mthds, inputs.json, and sets -L automatically — no need to specify them explicitly. This also avoids namespace collisions with other bundles.
Step 3: 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 4 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 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 inputs bundle <file>.mthds returns an empty inputs object ({}), inputs are ready — skip to Step 4.
Inputs required: If inputs exist, check inputs.json for readiness:
- Does
inputs.json exist in the bundle directory?
- If it exists, scan all
content values 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:
url fields pointing to local files that don't exist on disk
Readiness result:
- Ready:
inputs.json exists AND all content values are real (no placeholders, referenced files exist) → proceed to Step 4 with normal run
- Not ready:
inputs.json is missing, OR contains any placeholder values → proceed to Step 4 with dry-run fallback
Step 4: 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, use AskUserQuestion to present next steps:
- Question: "What would you like to do next?"
- Header: "Next step"
- Options:
- Prepare real inputs — "Use /mthds-inputs to fill in actual values, then re-run."
- Provide files — "Supply file paths for document/image inputs."
- Keep dry run — "Accept the dry-run result as-is."
Run modes reference
| Mode | Command | Use When |
|---|
| Dry run + mock inputs | mthds-agent 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 run bundle <bundle-dir>/ --dry-run | Validate input shapes without making API calls (auto-detects inputs.json) |
| Full run | mthds-agent run bundle <bundle-dir>/ | Production execution (auto-detects inputs.json) |
| Full run inline | mthds-agent run bundle <bundle-dir>/ --inputs '{"theme": ...}' | Quick execution with inline JSON inputs |
| Full run without graph | mthds-agent run bundle <bundle-dir>/ --no-graph | Execute without generating graph visualization |
| Full run with memory | mthds-agent 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-graph to 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.
mthds-agent run bundle <bundle-dir>/ --inputs '{"theme": {"concept": "native.Text", "content": {"text": "nature"}}}'
mthds-agent run bundle <bundle-dir>/
Step 5: 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
success wrapper. This is the primary output of the method's main concept. Parse the JSON directly for field access.
- With memory (
--with-memory): stdout has main_stuff (with json, markdown, html renderings) + 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.
5a. 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:
main_stuff is always the primary output for a completed run:
→ a value, or an explicit absence document for optional outputs
| 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 | Always (combined result) | main_stuff |
5b. Show the output content
In compact mode: show the JSON fields directly. For structured concepts, format for readability.
In --with-memory mode:
- Show
main_stuff.markdown directly — 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.json formatted for readability.
- If
main_stuff is an absence document (absent: true), show the absence reason and provenance instead of treating it as missing output.
For dry runs: Show the same output but clearly label it as mock/simulated data.
5c. Output file
- The CLI automatically saves the full JSON output next to the bundle (
live_run.json or dry_run.json).
- The output file path appears in runtime logs (stderr), not in compact stdout.
5d. Present graph files
- Graph visualizations are generated by default (
live_run.html / dry_run.html). Use --no-graph to disable.
- Live runs also write
live_run_graph.json (the graph spec) next to the bundle.
- The graph file paths appear in runtime logs (stderr), not in compact stdout.
5e. 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."
5f. Suggest next steps
- Re-run with different inputs
- Adjust prompts or pipe configurations if output quality needs improvement
Step 6: Handle Errors
If the run returns InferenceSetupRequiredError (error_domain: onboarding): This means inference has never been configured. This is the user's first live inference run — congratulate them on reaching this milestone, then immediately begin the /mthds-runner-setup flow inline (do not ask the user to type it separately). Follow the full process from that skill to guide them through Gateway or BYOK setup, then re-run the method.
For all other 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 run bundle <bundle-dir>/
Graph files (live_run.html / dry_run.html) are written to disk next to the bundle. Live runs additionally produce live_run_graph.json (the graph spec). 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 run method extract-terms --inputs data.json --with-memory \
| mthds-agent run method assess-risk --with-memory \
| mthds-agent 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-memory on intermediate steps to pass the full working memory envelope.
- The final step omits
--with-memory to produce compact output.
--inputs always 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
