anthropics/claude-code-monitoring-guide

1.4K

lines of other code

7 files

ABCDE

ease of change
for people* (4/10)

ABCDE

ease of change
for AI* (4/9)

0.06K

yaml

Rule-of-thumb estimates

Rebuild value

lines of main code per man-year per man-year currency

to rebuild

rebuild value

Maintenance effort

% of the rebuild value per year

per year to maintain

maintenance cost per year

Rules of thumb, not measurements: one man-year rebuilds about 10,000 lines of main code (design, testing and coordination included), and keeping a code base alive takes about 15% of its rebuild value per year (20 man-years of rebuild value need about 3 man-years of maintenance every year). Your changes are remembered in this browser for every report.

Ease of change*

4.6ABCDE

for people · measured on 4 of 10 sub-scores

Ease of change*

4.0ABCDE

for AI · measured on 4 of 9 sub-scores

Duplication

0%good

of main code duplicated

Large files

0%good

of main code in files > 500 lines

Goals

4 / 4good

controls in range

Ease of change*

How easily the code can be understood and changed, from 0 to 10. Other things equal, less code is easier and cheaper to change, for people and for agents. Both ratings weigh the same sub-scores: people struggle most with complex logic and knowledge held by few; agents pay for every line they read, copy duplicates and need tests to check their work. The total is a weighted geometric mean; above the weakest code sub-score + 4 only half of it counts, so one weak spot is not averaged away. Sub-scores are ordered by drag, how much the uncapped mean would rise if that sub-score were 10; click one to see why it matters. * A heuristic: compare repositories rather than read it as absolute. Set weights, or your own framework, in analysis.maintainabilityScores.

Human4.6ABCDE

Measured on 4 of 10 sub-scores (not measured: Unit size, Unit complexity, File complexity, Change entropy, Context per change, Knowledge spread).

Held down by Test code: above its score + 4, half counts.

Test code0.0−4.70 test lines per 100 main lines
For people: Tests document the intended behaviour and make changes safe.
For AI agents: Tests let an agent check its own work; without them its mistakes surface later, in review or in production.
Volume10.056 lines of main code
For people: More code is more to learn, search and keep in mind; onboarding and judging a change's impact slow down as it grows.
For AI agents: An agent sees only a slice at a time: the bigger the code base, the more it searches, and the likelier it misses relevant code or rewrites an existing helper.
Duplication10.00% of main code duplicated
For people: A fix in one copy must be repeated in all the others; a missed copy becomes a bug.
For AI agents: Agents copy the patterns they find, so duplicates multiply; a change to one copy misses the others, and every copy costs context.
File size10.00% of main code in files > 500 lines
For people: Large files are hard to navigate, mix responsibilities and attract merge conflicts.
For AI agents: Agents read whole files into their context: every change to a large file costs many tokens and crowds out other relevant code.

AI4.0ABCDE

Measured on 4 of 9 sub-scores (not measured: Unit size, Unit complexity, File complexity, Change entropy, Context per change).

Held down by Test code: above its score + 4, half counts.

Test code0.0−6.00 test lines per 100 main lines
For AI agents: Tests let an agent check its own work; without them its mistakes surface later, in review or in production.
For people: Tests document the intended behaviour and make changes safe.
Volume10.056 lines of main code
For AI agents: An agent sees only a slice at a time: the bigger the code base, the more it searches, and the likelier it misses relevant code or rewrites an existing helper.
For people: More code is more to learn, search and keep in mind; onboarding and judging a change's impact slow down as it grows.
Duplication10.00% of main code duplicated
For AI agents: Agents copy the patterns they find, so duplicates multiply; a change to one copy misses the others, and every copy costs context.
For people: A fix in one copy must be repeated in all the others; a missed copy becomes a bug.
File size10.00% of main code in files > 500 lines
For AI agents: Agents read whole files into their context: every change to a large file costs many tokens and crowds out other relevant code.
For people: Large files are hard to navigate, mix responsibilities and attract merge conflicts.

Where to look first

The most complex main files (no git history, so no change frequency).

1
otel-collector-config.yaml
34 LOC
2
dashboards.yaml
grafana/provisioning/dashboards/
11 LOC
3
prometheus.yml
11 LOC

Explore all files →

Standard analyses:
		Main Code: 56 LOC (3 files) = YAML (100%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 43 LOC (1); Other: 1,406 LOC (6);
		Duplication: 0%
		File Size: 0% long (>1000 LOC), 100% short (<= 200 LOC)
		Logical Component Decomposition: primary (2 components)
		Goals: Keep the system simple and easy to change (4)

Experimental analyses (less reliable heuristic analyses):
		Static Component Dependencies: primary (2 components)