GitHub Certified: Agentic AI Developer flashcards

32 cards. Read the term and the definition here. The deck at the top of this page is optional.

Copilot coding agent

An asynchronous GitHub agent that is assigned an issue, works in an ephemeral Actions-powered environment, and delivers its output as a draft pull request requiring human review.

Draft pull request

The default output form of an agent's work: a PR opened in draft state that signals in-progress authoring and must be marked ready before human review begins.

Agent steering channel

The issue or pull request comment thread where a human corrects an autonomous agent; comments posted there trigger new agent turns, making the thread the supervision interface.

Issue assignment permission

Only users with write access to a repository can assign issues to GitHub's coding agent, which prevents read-only or outside contributors from consuming repository compute.

Acceptance criteria

Explicit, checkable conditions written into an issue body that define when an autonomous agent's work is complete; ambiguity here is the leading source of agent rework.

Agent session log

The recorded transcript of an agent run, reachable from the pull request or the Actions run, used to diagnose why the agent made a particular change.

Human takeover trigger

A decision rule that a person takes over from the agent, typically invoked after two consecutive agent iterations fail the same required status check.

copilot-instructions.md

A repository-level custom instructions file stored at .github/copilot-instructions.md whose content is applied to every Copilot request made in that repository.

Path-specific instructions

Instruction files carrying an applyTo glob in their front matter, so guidance such as testing conventions applies only when the agent touches matching file paths.

AGENTS.md

A markdown file at the repository root giving agents build, test, and convention guidance; a widely supported convention for agent-facing repository documentation.

MCP server

A Model Context Protocol service that exposes tools and data to an agent; each added server increases the agent's capability and its attack surface simultaneously.

Least-privilege agent token

A fine-grained personal access token or GitHub App installation token scoped to a single repository with only the specific permissions the agent's assigned task genuinely requires.

Deny-by-default tooling

A configuration posture in which an agent's shell commands, network hosts, and external tools are blocked unless explicitly allowlisted, limiting the blast radius of misuse.

Pinned action version

Referencing a GitHub Action by its full commit SHA instead of a mutable tag, so an agent-driven workflow cannot silently pull in changed third-party code.

Outcome correctness

An evaluation dimension measuring whether the agent's change satisfies the issue's acceptance criteria and passes the repository's automated tests and required status checks.

Process quality

An evaluation dimension covering how a change was produced: diff size, files touched, convention adherence, and the absence of unrelated or cosmetic modifications.

Regression eval suite

A fixed set of representative agent tasks with known-good reference solutions, re-run whenever instructions, tools, or the underlying model are changed.

Rework rate

The share of agent-authored pull requests that need more than one review cycle before merge; a direct efficiency signal about agent output quality.

Claim-versus-check gap

The failure mode where an agent's written summary asserts tests passed while the actual check runs show failure; verify status checks, never the agent's prose.

Hallucinated dependency

An import or package introduced by an agent that does not exist in the project manifest or lockfile; a high-signal indicator of unreliable generated code.

Fan-out fan-in

An orchestration pattern that splits an epic into independent issues executed in parallel, then merges results; safe only when agent file scopes do not overlap.

Triage gate label

A label such as agent-ready that must be applied before assignment, preventing agents from starting underspecified, unapproved, or duplicative work.

Ephemeral run environment

A fresh, containerized, single-use environment provisioned for each agent run, with a clean checkout and no shared mutable state between runs.

Backpressure threshold

A cap on open agent pull requests awaiting review; when exceeded, new assignments pause so unreviewed code cannot accumulate faster than humans review it.

Idempotent dispatch

Designing agent triggers so a retried webhook or workflow run yields the same single pull request rather than duplicates, usually via unique keys or state checks.

Topological issue ordering

Sequencing agent tasks so dependent work begins only after prerequisite changes merge, preventing agents from building on code that does not yet exist.

Agent attribution

The property that every commit, pull request, and workflow run traces to the agent's distinct identity, enabling audit and clean separation from human actions.

Ruleset enforcement

Repository rules requiring passing status checks and human approval on the default branch; agents must not receive bypass, or required review becomes meaningless.

Prompt injection risk

The exposure created when an agent treats issue text, comments, or fetched content as instructions; containment depends on tool allowlists and least privilege.

Environment protection rule

A deployment gate requiring designated reviewers or a wait timer before an environment's secrets are released, keeping irreversible releases under human control.

Secret scanning push protection

A GitHub control that blocks commits containing detected credentials, preventing an agent from committing a token it read from its runtime environment.

Policy as code

Encoding agent-related governance in rulesets, CODEOWNERS, and required workflows so enforcement does not depend on reviewer memory or goodwill.