dry-run
Skill2 starsChanged 8 months agoMITView on GitHub
Internal dynos-work skill. Validate contract.json chaining across the skill pipeline. Checks that output_schema of each pipeline stage covers the required input_schema fields of the next stage. Runs only when the user explicitly types /dynos-work:dry-run; never auto-triggered from conversation.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- atinder-harika/reel-reactortheir own version, first seen Nov 8, 2026
- marcusgoll/Spec-Flowtheir own version, first seen Apr 23, 2026
- jitangupta/file-safety-guardtheir own version, first seen Feb 9, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- marcusgoll/Spec-Flow★ 94same name
- jitangupta/file-safety-guard★ 3same name
- atinder-harika/reel-reactor★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository34 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- auditSkill
- calibrationSkill
- dashboardSkill
- executeSkill
- execution/backend-executorSkill
- execution/data-executorSkill
- execution/db-executorSkill
- execution/infra-executorSkill
- execution/integration-executorSkill
- execution/ml-executorSkill
- execution/observability-executorSkill
- execution/refactor-executorSkill
- execution/release-executorSkill
- execution/security-executorSkill
- executionSkill
- execution/testing-executorSkill
- execution/ui-executorSkill
- globalSkill
- initSkill
- investigateSkill
- listSkill
- localSkill
- maintainSkill
- memorySkill
- planSkill
- registerSkill
- repairSkill
- residualSkill
- resumeSkill
- startSkill
- statusSkill
- trajectorySkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
16 rules. 0 are common, 6 are distinctive, and 10 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
10
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Treat missing or incompatible contract fields as real pipeline breakage, not paperwork.
- Distinctive: line 13
Do not infer compatibility from naming similarity alone.
- Distinctive: line 14
If a downstream stage depends on behavior the upstream contract does not guarantee, call it broken.
- Very specific: line 22
If any skill directory lacks a contract.json, emit a warning that names every specific directory:
- Very specific: line 51
Read the output_schema of stage N.
- Very specific: line 52
Read the input_schema of stage N+1.
- Very specific: line 54
Check if a field with a matching key exists in stage N's output_schema.
- Very specific: line 55
If the field exists, check that the type values are compatible (exact match or both resolve to the same base type).
- Very specific: line 56
If the field is missing from stage N's output_schema, record a FAIL with details.
- Distinctive: line 57
If the field exists but the type does not match, record a FAIL with details.
- Very specific: line 107
If an active or completed task exists in .dynos/, run the runtime contract validator against it to verify real artifacts match the declared …
- Distinctive: line 119
If all required chain links pass, print:
- Distinctive: line 124
If any required chain link fails, print:
- Very specific: line 131
Every skill should have a contract.json file in its skill directory (skills/<name>/contract.json).
- Very specific: line 174
Keep field names consistent across stages.
- Very specific: line 175
Use the source field to document where the data actually lives on disk or comes from at runtime.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
dynos-work: Dry Run
Validate that the contract.json files across all skills form a valid pipeline chain. This skill reads every skills/*/contract.json, determines the pipeline order, and verifies that each stage's outputs satisfy the next stage's required inputs.
Ruthlessness Standard
- Treat missing or incompatible contract fields as real pipeline breakage, not paperwork.
- Do not infer compatibility from naming similarity alone.
- If a downstream stage depends on behavior the upstream contract does not guarantee, call it broken.
What you do
Step 1 -- Discover contracts
- Scan all directories under
skills/in the project root. - For each directory, check if a
contract.jsonfile exists. - If any skill directory lacks a
contract.json, emit a warning that names every specific directory:WARNING: Missing contract.json in: skills/foo/, skills/bar/ - Parse each discovered
contract.jsonfile. If any file contains invalid JSON, report it as an error and skip that contract.
Step 2 -- Determine pipeline order
The linear pipeline chain is fixed:
start -> plan -> execute -> audit -> learnSkills that are NOT part of the linear pipeline (utility skills) are:
- status
- investigate
- resume
- repair
- execution
- dashboard
- dry-run
Utility skills have contracts but do not participate in linear chain validation. They should still be loaded and listed in the report.
Step 3 -- Validate chain links
For each consecutive pair in the pipeline (stage N -> stage N+1):
- Read the
output_schemaof stage N. - Read the
input_schemaof stage N+1. - For every field in stage N+1's
input_schemawhererequiredistrue:- Check if a field with a matching key exists in stage N's
output_schema. - If the field exists, check that the
typevalues are compatible (exact match or both resolve to the same base type). - If the field is missing from stage N's
output_schema, record a FAIL with details. - If the field exists but the type does not match, record a FAIL with details.
- Check if a field with a matching key exists in stage N's
- For optional fields (where
requiredisfalse), check availability but only emit an INFO-level note if missing, not a FAIL.
Important: Some inputs have source values that reference things outside the immediate predecessor (e.g., user prompt, filesystem paths, or outputs from earlier stages). When an input field's source explicitly references a specific origin other than the previous pipeline stage, note it but do not count it as a chain break. The chain validation focuses on whether the pipeline as a whole produces what downstream stages need.
Step 4 -- Generate report
Print a structured report with the following sections:
=== dynos-work Dry Run: Contract Chain Validation ===
Pipeline: start -> plan -> execute -> audit -> learn
--- Contracts Loaded ---
[OK] skills/start/contract.json
[OK] skills/plan/contract.json
...
[WARN] skills/dashboard/ -- missing contract.json
--- Chain Validation ---
start -> plan:
[PASS] manifest.json (object -> object)
[PASS] spec.md (string -> string)
[FAIL] design-decisions.md: present in plan input_schema (required: false) but missing from start output_schema [INFO]
...
plan -> execute:
[PASS] manifest.json (object -> object)
...
execute -> audit:
...
audit -> learn:
...
--- Summary ---
Pipeline stages validated: 4
Total required fields checked: NN
Passed: NN
Failed: NN
Warnings: NN
Result: PASS (or FAIL if any required field is missing/mismatched)Step 5 -- Runtime validation (optional)
If an active or completed task exists in .dynos/, run the runtime contract validator against it to verify real artifacts match the declared contracts:
"${CODEX_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-}}/bin/dynos" ctl validate-contract --skill start --task-dir .dynos/task-{id} --direction both --strict
"${CODEX_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-}}/bin/dynos" ctl validate-contract --skill execute --task-dir .dynos/task-{id} --direction both --strict
"${CODEX_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-}}/bin/dynos" ctl validate-contract --skill audit --task-dir .dynos/task-{id} --direction both --strictReport any mismatches between declared contracts and actual artifacts. This catches drift between what contracts promise and what skills actually produce.
Step 6 -- Exit
If all required chain links pass, print:
Dry run PASSED. All pipeline contracts are compatible.If any required chain link fails, print:
Dry run FAILED. See mismatches above.Contract Schema Reference
Every skill should have a contract.json file in its skill directory (skills/<name>/contract.json). The schema is:
{
"skill": "<skill-name>",
"description": "<what this skill does>",
"input_schema": {
"<field-name>": {
"type": "<string | object | array | boolean>",
"required": true | false,
"source": "<where this input comes from, e.g. '.dynos/task-{id}/manifest.json'>"
}
},
"output_schema": {
"<field-name>": {
"type": "<string | object | array | boolean>",
"description": "<what this output contains>"
}
}
}Field definitions
| Field | Required | Description |
skill | Yes | The skill name, must match the directory name |
description | Yes | Human-readable description of what the skill does |
input_schema | Yes | Map of field names to input descriptors |
input_schema.<field>.type | Yes | Data type: string, object, array, or boolean |
input_schema.<field>.required | Yes | Whether this input is mandatory for the skill to run |
input_schema.<field>.source | Yes | Where the input originates (file path pattern, user prompt, etc.) |
output_schema | Yes | Map of field names to output descriptors |
output_schema.<field>.type | Yes | Data type of the output |
output_schema.<field>.description | Yes | Human-readable description of the output content |
Pipeline vs. utility skills
- Pipeline skills (start, plan, execute, audit, learn) form a linear chain. The output_schema of each stage must cover the required input_schema fields of the next stage.
- Utility skills (status, investigate, resume, repair, execution, dashboard, dry-run) operate independently. They still need contracts for documentation and tooling, but they are not validated as part of the linear chain.
Tips for skill authors
- Keep field names consistent across stages. If
startoutputsmanifest.json, thenplanshould referencemanifest.jsonas an input, nottask_manifest. - Use the
sourcefield to document where the data actually lives on disk or comes from at runtime. - Mark fields as
required: falseif the skill can operate without them (graceful degradation). - The
typefield should match across producer and consumer. Ifstartoutputsmanifest.jsonas typeobject, thenplanshould expect typeobjectformanifest.json.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

