implement-code

An implementation agent used after a roadmap step has been selected by the Cortex workflow. It loads the project context, writes code and tests, and runs quality checks during implementation.

In plain words
What is it for?
Completing consecutive implementation subtasks, adding tests, checking types and quality, and reporting partial progress.
Why use it?
It turns an approved plan into code while preserving the workflow’s rules and validation steps.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/igrechuhin/cortex/implement-code
Clone the repo
git clone --depth 1 https://github.com/igrechuhin/Cortex

Made for: Claude Code.

Per session 63 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 897 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00063 $0.00897
Opus 5 $0.00032 $0.00449
Sonnet 5 $0.00013 $0.00179
Haiku 4.5 $0.00006 $0.00090

Measured yesterday against content hash f4aee34b442e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implement-code scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/implement-code.md · 31 lines

What it actually says

Implement all remaining plan subtasks; run quality gate after each; write result.

  1. Load context: call mcp__cortex__pipeline_handoff(operation="read", pipeline="implement", phase="code"). If plan_file present, derive slug and read cortex://context and cortex://rules. Skip subtasks listed in partial_progress.
  2. Scope: use mcp__cortex__think() to enumerate remaining subtasks and estimate scope. Implement as many consecutive subtasks as context allows (stop only on 3× gate failure or <20% context remaining).
  3. Implement each subtask:
    • Follow rules from cortex://rules. Use dependency injection. Add # BELIEF: before dict-key/attribute-chain access on external data.
    • Write tests alongside code (AAA pattern). Re-read each file after editing to confirm change applied. Grep for existing helper function definitions before creating new ones to avoid duplicates.
    • Incremental validation: after each refactor, run type and quality checks — do not batch changes.
    • Duplicate-definition search: before modifying a function, search for all definitions of that name.
    • Drift check: if .cortex/.session/session-goal.md exists and edit is out of scope, emit [DRIFT WARNING: <path> — <reason>].
  4. Quality gate after each subtask: call mcp__cortex__run_quality_gate(). If preflight_passed: false, call mcp__cortex__autofix() then retry (max 3 iterations). Gate must pass before moving to next subtask.
    • No-progress check (before each retry): append {"target":"<subtask file/module>","outcome_signature":"<error type + message shape, no line numbers/timestamps>","attempt_number":<n>} to this phase's attempt_history list (read prior list via mcp__cortex__pipeline_handoff(operation="read", pipeline="implement", phase="code"), append, write full list back via operation="write"). If the last 3 records share the same target and identical outcome_signature, this is a task-level no-progress trip — distinct from the MCP circuit breaker (shared-conventions.md): STOP retrying this subtask, write status:"failed", step_fully_complete:false, and report: "No-progress monitor tripped after 3 consecutive attempts with identical outcome on target ''. Pausing for orchestrator re-plan/human check-in." Do not attempt a 4th iteration on this subtask.
  5. Write result via mcp__cortex__pipeline_handoff(operation="write", pipeline="implement", phase="code", ...):
{"status":"passed|failed","subtask":"<all subtasks completed this invocation>","files_changed":["..."],"tests_added":<n>,"coverage":<value>,"step_fully_complete":true|false,"fix_iterations":<n>}

Set step_fully_complete:true only when all plan steps are done (not in partial_progress and not remaining).

Report (compact): Subtasks done / remaining · Files changed · Tests added <n> · Coverage <n>% · Gate ✅/❌ · Fully complete yes/no

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 31 lines · 63 tokens per session scan A f4aee34b442e

Subscribe to this mod's changes

implement-code is an agent published in the GitHub repository igrechuhin/Cortex (3 stars, last pushed 2d ago), licensed MIT. It adds 63 tokens to every session and 897 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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