How to Chain Multiple Agent Skills in Claude Code (2026)

One skill does one job. The interesting work starts when you get three of them to hand off to each other in a single session – research a topic, draft a document, then export it to PDF, with no copy-paste in between. That chaining is the part most people miss, because they install skills and use them one at a time like separate apps.

Claude Code already composes skills automatically when the job needs it. Your job is to set the work up so the agent chains the right ones in the right order, and in knowing when a chain will fight itself. Here is how it works and where it breaks.

How chaining actually happens

Skills are loaded on demand. Each has a description telling the agent when it applies, and when your request touches two domains, the agent pulls in both. Ask it to "research the 2026 EV market and put the findings in a spreadsheet," and it reaches for a research skill and a spreadsheet skill in sequence without you naming either. The chaining is model-driven, not a config file.

That is the good news and the trap. Model-driven means flexible, and it also means you get less deterministic ordering than a hard-coded pipeline. For a repeatable production job, that non-determinism is the thing you design around.

The two ways to chain

Implicit chaining: let the agent decide

For ad-hoc work, just describe the outcome and let the agent sequence the skills. This is genuinely how most chaining should happen – you are not smarter than the model about which skill fits a subtask you did not anticipate.

The one habit worth keeping: describe the outcome, not the tools. "Give me a competitor analysis as a formatted PDF" lets the agent chain research, drafting, and pdf-tools on its own. "Use the research skill then the PDF skill" over-constrains it and you lose the flexibility that made skills worth using. Trust the model on the ordering unless you have a reason not to.

Explicit chaining: when order is load-bearing

Some sequences have a required order, and getting it wrong produces silent garbage. A slop-scrubbing pass has to run after the draft exists, not before. A schema-validation step has to run before you publish, not after. When order is load-bearing, spell it out:

"First, use deep-research to gather sources on the 2026 IDX market. Then draft a 1,000-word summary. Then run the anti-slop pass on the draft. Only after that passes, export to PDF."

Numbering the steps and adding the gate – "only after that passes" – turns a loose suggestion into a sequence the agent respects. This is the difference between a chain that works once and one that works every Tuesday.

Orchestrated chaining: a skill that calls skills

The sturdiest pattern for a job you run repeatedly is a parent skill whose whole purpose is to run the others in a fixed order. The skill-creator skill helps you build these. Your orchestrator skill’s instructions say, in effect: run research, then draft, then scrub, then export, and here is what to do if a step fails.

/plugin marketplace add anthropics/skills
/plugin install skill-creator

This costs you an afternoon of setup and buys you determinism. For anything that ships to users on a schedule – a daily report, a content pipeline – that trade is worth making. For a one-off, it is over-engineering.

Passing data cleanly between steps

The handoff between two skills is where chains earn or lose their reliability, and files are the underrated fix. When step one produces something step two needs verbatim - a full transcript, a long dataset, a draft you cannot afford to have paraphrased - have the agent write it to a file, then have the next step read that file. Passing it through the conversation invites the model to summarize or truncate it on the way. A file on disk arrives intact.

This also makes a chain restartable. If the export step fails at the end of a four-skill run, you do not want to re-run the expensive research step. Write each stage’s output to disk and you can resume from the last good file instead of starting over. For any chain with a slow or costly step early on, this alone justifies the small amount of extra structure.

Where chains break

Three failure modes come up again and again.

Context bloat is the first. Every skill a chain loads eats context. Chain six heavy skills in one session and the agent starts forgetting what happened in step two by the time it reaches step five. Keep chains to the skills the job needs, and split genuinely large jobs across sessions.

Conflicting instructions are the second. Two skills can carry contradictory rules – one says use bullet points, another says prose only. The agent resolves this unpredictably. If you chain two skills that overlap in domain, read both SKILL.md files and know which rules collide before you rely on the output.

Silent step-skipping is the third and worst. In implicit chaining, the agent sometimes decides a step is unnecessary and drops it. Your slop pass never ran, but the PDF looks fine, so you ship unscrubbed text. The fix is the explicit gate: name the step and require it to pass before the next one starts.

Debugging a chain that produced garbage

When a chain gives you a bad result, the instinct is to blame the skills. The cause is almost always the handoff, not the skill. Three checks find it fast.

First, ask the agent what it did. "Which skills did you use, in what order, and did any step get skipped?" The agent will usually tell you it dropped the validation step or ran the export before the draft was final. That answer points straight at the missing gate.

Second, look at what one step passed to the next. A research skill that returned a vague summary hands the drafting skill nothing concrete to work with, and the draft comes out thin. The fix is upstream: tighten the first step’s output before blaming the second. Garbage in, garbage forwarded.

Third, check for a context wall. If the chain was long and the final output ignores something established early, the agent ran out of room to hold it all. Split the chain: run research and drafting in one session, save the draft to a file, then scrub and export in a fresh session that reads the file. Skills compose within a session, but a file on disk is the most reliable handoff between sessions.

A chain I actually run

Research to published article: deep-research gathers and verifies sources, a drafting pass writes the piece, an anti-slop pass scrubs it to a minimum score, and only then does it get formatted. Four skills, one session, explicit order with a gate on the slop score. It fails maybe one run in ten, always at the slop gate, which is exactly where I want it to fail – loudly, before publishing, not quietly after.

If you are new to skills, start with how to write your first Claude Code skill, and before you install anything from outside the official marketplace, run through how to audit agent skill security. For the bigger picture on how skills relate to MCP servers, see skills vs MCP servers vs plugins.

FAQ

Do I have to manually tell Claude Code to chain skills? No. It composes skills automatically based on the request. You only need explicit ordering when a step must run before or after another and the wrong order produces bad output.

How many skills can I chain in one session? There is no hard limit, but context is finite. Past four or five heavy skills the agent starts losing track of earlier steps. Split large jobs across sessions instead of forcing everything into one.

What happens when two skills give conflicting instructions? The agent resolves it unpredictably. Read both SKILL.md files before chaining overlapping skills, and if they truly conflict, pick one or write a wrapper that sets the precedence explicitly.

Can I build a skill that runs other skills in order? Yes. A parent orchestrator skill can specify a fixed sequence and failure handling. Use skill-creator to build one when you need a repeatable pipeline. It is over-engineering for one-off tasks.

Why did my chain skip a step? Implicit chaining lets the agent drop steps it judges unnecessary. Add an explicit gate – name the step and require it to complete before the next one – to force it to run.