Skill chaining for complex workflows

Single skills are powerful; chaining them is how you get complex workflows. A morning brief might chain "get calendar" → "get tasks" → "get document status" → "compose brief" → "send to Slack." Each step is one skill; the orchestrator passes data and handles failures. This guide covers skill chaining for complex workflows: how to design the chain, pass data between skills, handle errors, and where document and PDF pipelines (e.g. iReadPDF) fit so US professionals get reliable end-to-end automation.

Summary Design chains as a clear sequence of skills with defined inputs and outputs. Pass outputs as inputs to the next skill using stable keys (e.g. calendar_events, doc_summaries). On failure, decide retry, skip, or abort. When document workflows are in the chain, treat "get document summary" or "get document status" as a step that other skills consume—so iReadPDF and your doc pipeline slot in as a single, reusable link.

Table of Contents

• Why Chain Skills
• Designing the Chain
• Data Passing Between Skills
• Where Document Pipelines Fit
• Error Handling and Recovery
• Orchestration Patterns
• Example End-to-End Chain
• Conclusion

Why Chain Skills

Chaining keeps each skill simple and composable while achieving complex behavior.

• Reuse. You don't build "morning brief that also does calendar, tasks, and docs" as one monolith. You reuse "get calendar," "get tasks," "get document status," and "compose brief" in other chains (e.g. meeting prep, end-of-day summary).
• Testability. You can test each skill in isolation and then test the chain with mock data. When the brief is wrong, you know which link (e.g. doc status) to fix.
• Clarity. The chain is a readable sequence: "fetch data → enrich with docs → compose → deliver." New team members or tools (e.g. iReadPDF) plug in at the right step.
• Flexibility. You can swap or reorder steps (e.g. add "get weather" or "get doc summaries" only when include_docs is true) without rewriting the whole workflow.

For US professionals running daily briefs, meeting prep, and task suggestion, skill chaining turns a set of small skills into one coherent workflow.

Designing the Chain

A chain is an ordered sequence of steps. Each step is one skill; the output of step N can feed step N+1.

1. List the outcome you want. Example: "Every morning at 7 AM I get a brief with calendar, tasks, and document queue, sent to Slack."
2. Break it into steps. What data do you need first? Calendar, tasks, document status. Then what? Compose a message from that data. Then? Send to Slack. So: get_calendar → get_tasks → get_document_status → compose_brief → send_to_slack.
3. Define inputs and outputs per step. get_calendar needs time_range; it outputs calendar_events. get_document_status needs nothing (or user_id); it outputs doc_queue. compose_brief needs calendar_events, task_list, doc_queue; it outputs brief_text. Clear contracts prevent "why did the next step get the wrong shape?" bugs.
4. Mark optional steps. If "get document status" is optional (e.g. when include_docs is false), the orchestrator skips it and passes an empty doc_queue to compose_brief. The compose skill should accept "no docs" and still produce a valid brief.

When document workflows are involved, "get document status" and optionally "get document summary" (or "ensure summaries exist via iReadPDF") are explicit steps. The rest of the chain doesn't open PDFs; they just consume the output of those steps.

Data Passing Between Skills

The orchestrator (or workflow engine) is responsible for passing data from one skill to the next.

• Stable output keys. Each skill returns a structured result with fixed keys. Examples: calendar_events, task_list, doc_queue, doc_summaries, brief_text. The next skill's input spec says "expects calendar_events (array), doc_queue (array)." The orchestrator maps previous outputs to those keys.
• No mutation of shared state unless intended. Prefer "skill returns X; orchestrator passes X to next skill" over "skill reads and writes global state." That way the chain is reproducible and testable. Exception: a dedicated "update memory" or "update doc status" skill that is explicitly a side-effect step.
• Document data in one format. When a step returns doc_summaries (e.g. from your iReadPDF pipeline or from memory), use one schema (title, summary, key_points, status) so every downstream skill knows what to expect. The orchestrator doesn't transform doc data; it just passes it.
• Context object. Some systems use a single "context" object that accumulates: after step 1 it has calendar_events; after step 2 it has calendar_events + task_list; after step 3 it has + doc_queue; etc. Downstream skills read only what they need from context. That works as long as key names are stable and documented.

For US professionals, clear data passing means you can debug "brief had wrong doc list" by checking the output of get_document_status and the input of compose_brief, without tracing through one big script.

Where Document Pipelines Fit

Document and PDF workflows are one or more steps in the chain. They should not be duplicated inside every consumer skill.

• Step: get document status. A skill that reads from memory or your doc store and returns doc_queue (list of docs with status: to_summarize, summarized, to_sign, signed). No PDF opening here—just metadata and, if available, pointers to summaries already produced (e.g. by iReadPDF).
• Step: get document summaries (optional). If the workflow needs full summaries (e.g. for meeting prep), a step that fetches summaries for given doc IDs—from cache/memory or by triggering your PDF pipeline. That step's output is doc_summaries in the standard format; downstream skills only consume it.
• Async or pre-run. Sometimes summarization happens outside the chain (e.g. you run iReadPDF when you add a PDF; summaries are written to memory). Then the chain's "get document status" and "get document summaries" steps just read that pre-populated data. The "document pipeline" is a separate process that feeds the chain, not necessarily a synchronous step inside it.
• Single format. Whether summaries are produced by iReadPDF or another tool, the chain and all skills should agree on one summary schema. Then compose_brief, meeting_prep, and task_suggestion all work with the same doc_summaries shape.

So: document pipelines are either (1) a step in the chain that returns doc_queue and/or doc_summaries, or (2) an external process that writes to memory/store that those steps read. Either way, the rest of the chain is document-format agnostic except for consuming that structure.

Error Handling and Recovery

When one skill in the chain fails, the whole workflow shouldn't silently break.

• Explicit failure contract. Each skill should return a success/failure indicator and, on failure, a reason (e.g. "calendar API timeout," "no doc summary for id X"). The orchestrator then decides what to do.
• Options: retry, skip, or abort. Retry: transient errors (e.g. network). Skip: optional step (e.g. get_document_status); if it fails, pass empty doc_queue and continue. Abort: critical step (e.g. compose_brief); notify and stop.
• Fallbacks. For optional steps, have a fallback value. If get_document_status fails, pass doc_queue: [] so compose_brief still runs. Document in the chain spec: "Step get_document_status: on failure, pass empty doc_queue."
• Logging. Log each step's input and output (or at least success/failure and duration). When "brief was empty" happens, you can see whether get_calendar returned empty, get_document_status failed, or compose_brief received data but produced nothing. That makes debugging skill chains tractable.

For document steps, distinguish "no docs" (success, empty list) from "failed to fetch doc status" (error, use fallback or abort depending on policy). iReadPDF or your pipeline may have its own retry logic; the chain only needs to know "summaries available or not" for the current run.

Orchestration Patterns

Common patterns for chaining skills:

| Pattern | When to use | Example | |---------|-------------|---------| | Linear | Steps run in order; each needs the previous. | get_calendar → get_tasks → get_doc_status → compose_brief → send. | | Parallel | Steps are independent; run in parallel, then merge. | get_calendar and get_tasks and get_doc_status in parallel → compose_brief (needs all three). | | Conditional | Skip or add steps based on input. | If include_docs, run get_doc_status; else pass empty. | | Loop | Run one skill per item (e.g. per doc). | For each doc in queue, get_summary (or ensure summarized via iReadPDF); then aggregate and pass to compose. |

For many US-professional workflows, linear is enough. Parallel saves time when calendar, tasks, and doc status can be fetched independently. Conditional keeps the same chain flexible (e.g. brief with or without docs). Document the pattern you use so future changes (e.g. adding a new step) stay consistent.

Example End-to-End Chain

Goal: Morning brief with calendar, tasks, and document queue, sent to Slack at 7 AM.

| Step | Skill | Input (from) | Output (to) | |------|--------|--------------|-------------| | 1 | get_calendar | time_range (config) | calendar_events | | 2 | get_tasks | user_id (config) | task_list | | 3 | get_document_status | user_id (config) or memory | doc_queue | | 4 | compose_brief | calendar_events, task_list, doc_queue, preferences | brief_text | | 5 | send_to_slack | brief_text, channel (config) | success/failure |

Document flow: doc_queue is populated by your doc pipeline (e.g. you summarize PDFs in iReadPDF and update memory; get_document_status reads that). compose_brief receives doc_queue and, if your format includes summary snippets, can show "2 to summarize, 1 to sign" and optionally mention "summarize in iReadPDF first." No PDF handling inside compose_brief—only structured data from the previous step.

If step 3 fails: pass doc_queue: [] and continue so you still get a brief; log the failure for follow-up. If step 4 fails: abort and notify; no point sending an empty or broken brief.

Conclusion

Skill chaining for complex workflows means designing a clear sequence of skills with defined inputs and outputs, passing data with stable keys, and handling errors with retry/skip/abort and fallbacks. Document pipelines fit as dedicated steps (get document status, get document summaries) or as external processes that feed the chain; either way, use one summary format (e.g. from iReadPDF) so every downstream skill stays in sync. For US professionals, that's how you get reliable, maintainable automation from reusable skills.

Ready to plug your document pipeline into a chain? Use iReadPDF for summarization and keep doc status and summaries in a standard format—then add get_document_status and optional get_document_summaries as steps in your workflow so the rest of the chain runs on clean, consistent doc data.