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fieldflow-cli

Use FieldFlow to inspect and reduce noisy JSON CLI output before it reaches model context. Trigger for read-only external CLI tasks likely to return large structured output, especially logs, list, describe, get, read, query, search, metrics, or status commands from tools like gcloud, gh, kubectl, aws, or similar CLIs that can emit JSON. Prefer `fieldflow-cli inspect` first, then rerun with explicit `--field` selectors. Do not use for tiny local commands, text-only commands, or mutating commands unless explicitly asked.

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name fieldflow-cli description Use FieldFlow to inspect and reduce noisy JSON CLI output before it reaches model context. Trigger for read-only external CLI tasks likely to return large structured output, especially logs, list, describe, get, read, query, search, metrics, or status commands from tools like gcloud, gh, kubectl, aws, or similar CLIs that can emit JSON. Prefer `fieldflow-cli inspect` first, then rerun with explicit `--field` selectors. Do not use for tiny local commands, text-only commands, or mutating commands unless explicitly asked. FieldFlow CLI Use this skill to keep large JSON CLI output out of model context. Qualify The Command Use fieldflow-cli only when all of these are true: The command is read-only. The command is external or service-facing, not a tiny local shell command. The command can emit JSON on stdout. The expected output is likely large enough that raw output would pollute context. Do not use this skill for commands like pwd , date , ls , git status , rg , or any mutating command such as deploy , apply , delete , or create . Inspect First Run fieldflow-cli inspect before choosing selectors unless you already have a manifest for the exact same wrapped command. fieldflow-cli inspect --sample-items 100 -- <wrapped command > The inspect step writes a compact field catalog under .fieldflow/inspect/ and prints the manifest to stdout. Treat that manifest as the source of truth for valid selectors. The manifest is deterministic and intentionally small: path types It does not store raw command output. Pick Minimal Fields Choose the smallest field set that answers the user’s question. Prefer fields like: timestamps severity or status identifiers or names URLs concise message fields latency, count, or state fields Avoid broad selectors such as [] or whole nested objects unless the task truly needs them. Run The Reduced Command After choosing selectors, rerun the command through fieldflow-cli . fieldflow-cli \ --field "[].timestamp" \ --field "[].severity" \ --field "[].jsonPayload.message" \ -- \ <wrapped command > If the result is too narrow, broaden the selectors and rerun the reduced call. Do not fall back to raw output unless the user explicitly asks for it. JSON Output Rules Prefer the CLI’s native JSON mode: gcloud : --format=json kubectl : -o json gh : --json ... aws : JSON is already standard, or use --output json when needed If the command cannot emit JSON, do not use this skill. Gcloud Example For noisy Cloud Run request or error logs: fieldflow-cli inspect --sample-items 100 -- \ gcloud logging read \ 'resource.type="cloud_run_revision" AND resource.labels.service_name="program-api-service" AND severity>=ERROR' \ --project=train-3328b \ --freshness=24h \ -- limit =2000 \ --format=json Then reduce to the smallest useful fields, for example: fieldflow-cli \ --field "[].timestamp" \ --field "[].severity" \ --field "[].httpRequest.requestMethod" \ --field "[].httpRequest.requestUrl" \ --field "[].httpRequest.status" \ --field "[].httpRequest.latency" \ -- \ gcloud logging read \ 'resource.type="cloud_run_revision" AND resource.labels.service_name="program-api-service" AND severity>=ERROR' \ --project=train-3328b \ --freshness=24h \ -- limit =2000 \ --format=json
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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